Figma Aktienkurs
📊 Peer Group
📈 Was ist das?
Die Peer Group sind die Unternehmen mit dem ähnlichsten Geschäftsmodell. Sie dienen als Vergleichsmaßstab, um eine Aktie einzuordnen.
🧮 Wie wird sie ausgewählt?
Nach Ähnlichkeit des Geschäftsmodells, also Unternehmen aus derselben Branche, mit vergleichbaren Produkten und einer ähnlichen Kundengruppe. Nur so vergleichst du Äpfel mit Äpfeln.
🏛️ Wofür ist sie wichtig?
Ob eine Aktie günstig oder teuer ist, lässt sich am ehesten im Vergleich beurteilen. Ein KGV von 18 oder ein EV/FCF von 20 wirkt je nach Maßstab günstig oder teuer. Die Peer Group liefert dabei den treffsichersten Maßstab: Unternehmen mit ähnlichem Geschäftsmodell, die denselben Bedingungen unterliegen.
🎯 Was bedeutet das für Anleger?
Liegt eine Kennzahl unter dem Peer-Durchschnitt, ist die Aktie relativ günstiger bewertet, über dem Durchschnitt entsprechend teurer. Ein Abschlag zur Peer Group kann eine Chance sein, aber auch einen Grund haben (zum Beispiel geringeres Wachstum). Der Vergleich ist ein Startpunkt, kein Urteil.
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📘 Marktkapitalisierung
📈 Was ist das?
Die Marktkapitalisierung zeigt, wie viel ein Unternehmen laut Börse aktuell wert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft Unternehmen in Größenklassen (Large, Mid, Small Cap) einzuordnen und gibt Hinweise auf Marktmacht und Stabilität.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Große Unternehmen gelten als stabiler, zahlen oft Dividenden, wachsen aber langsamer.
- Kleine Firmen können stärker wachsen, sind aber schwankungsanfälliger.
- Die Marktkapitalisierung ist ein guter Indikator für Unternehmensgröße, aber kein Maß für Unter- oder Überbewertung.
📘 Enterprise Value (Unternehmenswert)
📈 Was ist das?
Der Enterprise Value (EV) zeigt, was ein Unternehmen tatsächlich kostet, wenn man es komplett übernehmen würde – inklusive Schulden und abzüglich Cash.
🧮 Wie wird es berechnet?
(= Marktkapitalisierung + Nettoverschuldung)
🏛️ Wofür ist es wichtig?
Der EV ist eine realistischere Bewertungsbasis als die Marktkapitalisierung, da er die Kapitalstruktur berücksichtigt. Er ist Grundlage für Kennzahlen wie EV/FCF oder EV/Sales.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Der Enterprise Value zeigt, was ein Unternehmen tatsächlich wert ist – unabhängig davon, wie es finanziert ist.
- Er ist besonders wichtig für professionelle Investoren, da er eine objektivere Grundlage für Bewertungsvergleiche bietet als die Marktkapitalisierung allein.
- Ein Unternehmen mit hoher Verschuldung erscheint im EV teurer, eines mit viel Cash günstiger – auch wenn sie an der Börse gleich viel wert sind.
📘 Nettoverschuldung
📈 Was ist das?
Die Nettoverschuldung zeigt, wie viele Schulden nach Abzug des verfügbaren Cashs tatsächlich verbleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie zeigt, wie stark ein Unternehmen von Fremdkapital abhängig ist – und wie gut es in der Lage ist, seine Schulden kurzfristig zu bedienen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine niedrige oder negative Nettoverschuldung bedeutet hohe finanzielle Stabilität.
- Unternehmen mit viel Cash und geringer Verschuldung sind besser gerüstet für Krisen.
- Eine hohe Nettoverschuldung erhöht das Risiko – besonders bei steigenden Zinsen oder konjunkturellen Schwächen.
📘 Cash
📈 Was ist das?
Der Cashbestand zeigt, wie viele liquide Mittel einem Unternehmen sofort zur Verfügung stehen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Er gibt Auskunft über die finanzielle Flexibilität: Ein hoher Cashbestand ermöglicht Investitionen, Rückkäufe oder Krisenresistenz.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Cashbestand zeigt finanzielle Stärke und Handlungsspielraum.
- Cash kann für Investitionen, Schuldentilgung oder Aktienrückkäufe genutzt werden.
- Allerdings: Zu viel ungenutztes Kapital kann auch auf mangelnde Investitionsideen hinweisen.
📘 Anzahl ausstehender Aktien
📈 Was ist das?
Die Anzahl ausstehender Aktien gibt an, wie viele Aktien eines Unternehmens aktuell im Umlauf sind und von Investoren gehalten werden.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie ist die Grundlage für viele Kennzahlen wie Gewinn je Aktie (EPS), Marktkapitalisierung oder KGV.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Je weniger Aktien im Umlauf sind, desto höher fällt z. B. der Gewinn je Aktie aus – wichtig für Bewertung und Dividendenrendite.
- Aktienrückkäufe verringern die Anzahl ausstehender Aktien – und steigern den Wert je Aktie.
- Kapitalerhöhungen haben den gegenteiligen Effekt: mehr Aktien → Verwässerung der bestehenden Anteile.
📘 Kurs-Gewinn-Verhältnis (KGV)
📈 Was ist das?
Das KGV zeigt, wie oft der Gewinn pro Aktie im aktuellen Aktienkurs enthalten ist – also wie „teuer“ eine Aktie im Verhältnis zum Gewinn ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KGV gehört zu den bekanntesten Bewertungskennzahlen. Es hilft Anlegern einzuschätzen, ob eine Aktie im Vergleich zu ihrem Gewinn eher günstig oder teuer erscheint.
🧮 Berechnung
📊 KGV (TTM) = bezogen auf den Gewinn der letzten 12 Monate (Trailing Twelve Months):🎯 Was bedeutet das für Anleger?
- Ein niedriges KGV kann auf eine günstige Bewertung hindeuten – oder auf Probleme im Geschäftsmodell.
- Ein hohes KGV kann Wachstumserwartungen widerspiegeln – oder eine überbewertete Aktie.
📘 Kurs-Umsatz-Verhältnis (KUV)
📈 Was ist das?
Das KUV zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen – unabhängig vom Gewinn.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KUV ist besonders bei wachstumsstarken oder noch nicht profitablen Unternehmen hilfreich. Es zeigt, wie hoch der Umsatz an der Börse bewertet wird.
🧮 Berechnung
Marktkapitalisierung = 11,50 Mrd. $ | Umsatz (TTM) = 1,28 Mrd. $
Marktkapitalisierung = 11,50 Mrd. $ | Umsatz erwartet = 1,49 Mrd. $
🎯 Was bedeutet das für Anleger?
- Ein niedriges KUV kann auf Unterbewertung hindeuten – oder auf schwache Margen.
- Ein hohes KUV kann hohe Erwartungen widerspiegeln – oder übermäßigen Optimismus.
- Besonders sinnvoll bei Wachstumsunternehmen, bei denen der Gewinn oder Free Cashflow (noch) keine Aussagekraft hat.
📘 Unternehmenswert zu Umsatz (EV/Sales)
📈 Was ist das?
EV/Sales zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen, wenn man auch Schulden und Cash berücksichtigt – es ist eine kapitalstrukturbereinigte Version des KUV.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Diese Kennzahl eignet sich besonders für den Vergleich von Unternehmen mit unterschiedlicher Verschuldung – sie zeigt, wie teuer ein Unternehmen tatsächlich im Verhältnis zum Umsatz ist.
🧮 Berechnung
Enterprise Value = 9,81 Mrd. $ | Umsatz (TTM) = 1,28 Mrd. $
Enterprise Value = 9,81 Mrd. $ | Umsatz erwartet = 1,49 Mrd. $
🎯 Was bedeutet das für Anleger?
- EV/Sales ist neutral gegenüber der Kapitalstruktur und eignet sich gut für Unternehmensvergleiche.
- Ein niedriges Verhältnis kann auf eine günstig bewertete Aktie hindeuten – ein hohes Verhältnis auf hohe Erwartungen oder Überbewertung.
- Besonders nützlich bei wachstumsstarken, noch nicht profitablen Firmen.
📘 Unternehmenswert zu Free Cashflow (EV/FCF) | ex SBC
📈 Was ist das?
EV/FCF setzt den Unternehmenswert eines Unternehmens ins Verhältnis zu seinem Free Cashflow. Die Kennzahl zeigt damit, mit welchem Vielfachen des aktuellen Free Cashflows ein Unternehmen bewertet wird. EV/FCF ex SBC berücksichtigt zusätzlich aktienbasierte Vergütungen (Stock-Based Compensation, SBC). SBC verursacht zwar keinen direkten Cash-Abfluss, kann bestehende Aktionäre jedoch durch die Ausgabe zusätzlicher Aktien verwässern. Deshalb wird SBC bei dieser Variante vom Free Cashflow abgezogen.
🧮 Wie wird es berechnet?
EV/FCF ex SBC = Enterprise Value ÷ (Free Cashflow (TTM) − SBC)
🏛️ Wofür ist es wichtig?
EV/FCF ermöglicht eine Bewertung auf Basis des Free Cashflows und ergänzt damit gewinnbasierte Bewertungskennzahlen wie das KGV. Die Variante ex SBC berücksichtigt zusätzlich die wirtschaftliche Belastung durch aktienbasierte Vergütungen und ermöglicht dadurch eine konservativere Betrachtung aus Sicht der Aktionäre.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriges EV/FCF bedeutet, dass der Unternehmenswert im Verhältnis zum aktuellen Free Cashflow niedrig ist. Die Ursachen dafür sollten jedoch immer im Unternehmens- und Branchenkontext betrachtet werden.
- Ein hohes EV/FCF bedeutet, dass der Unternehmenswert im Verhältnis zum aktuellen Free Cashflow hoch ist. Das kann beispielsweise auf hohe Wachstumserwartungen oder eine vorübergehend schwache Cash-Generierung zurückzuführen sein.
- Bei positiver SBC und positivem bereinigtem Free Cashflow fällt EV/FCF ex SBC in der Regel höher aus als das klassische EV/FCF.
- Besonders aussagekräftig ist die Kennzahl bei Unternehmen mit relativ stabilen und gut einschätzbaren Cashflows.
- Bei negativem oder sehr niedrigem Free Cashflow ist EV/FCF nur eingeschränkt aussagekräftig und sollte nicht wie ein gewöhnliches Bewertungsmultiple interpretiert werden.
📘 Kurs-Buchwert-Verhältnis (KBV)
📈 Was ist das?
Das KBV zeigt, wie hoch der Marktwert eines Unternehmens im Verhältnis zu seinem bilanziellen Eigenkapital ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KBV ist besonders bei Substanzwerten (z. B. Banken, Industrie) relevant. Es hilft Anlegern zu erkennen, ob ein Unternehmen unter oder über seinem buchhalterischen Vermögen bewertet ist.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein KBV unter 1 kann auf Unterbewertung oder schwache Rentabilität hindeuten.
- Ein KBV über 1 zeigt, dass der Markt dem Unternehmen Mehrwert über den Buchwert hinaus zuschreibt (z. B. Marken, Patente, Wachstum).
- Das KBV eignet sich besonders gut für Unternehmen mit stabilen, materiellen Vermögenswerten.
📘 Eigenkapitalquote
📈 Was ist das?
Die Eigenkapitalquote zeigt, wie hoch der Anteil des Eigenkapitals an der Bilanzsumme eines Unternehmens ist – also wie stark es sich aus eigenen Mitteln finanziert.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Eine hohe Eigenkapitalquote steht für finanzielle Stabilität, Krisenfestigkeit und gute Bonität. Sie ist besonders relevant bei der Beurteilung der Verschuldung.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalquote signalisiert finanzielle Stabilität – besonders in Krisenzeiten.
- Ein niedriger Wert kann auf ein höheres Risiko oder eine aggressive Verschuldung hinweisen.
- Wichtig: Die Eigenkapitalquote sollte immer gemeinsam mit der Eigenkapitalrendite betrachtet werden. Nur so lässt sich beurteilen, ob ein Unternehmen nicht nur solide, sondern auch effizient wirtschaftet.
📘 Eigenkapitalrendite (ROE)
📈 Was ist das?
Die Eigenkapitalrendite zeigt, wie effizient ein Unternehmen mit dem Kapital seiner Aktionäre arbeitet – also wie viel Gewinn es pro Euro Eigenkapital erwirtschaftet.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Eigenkapitalrendite ist eine zentrale Rentabilitätskennzahl. Sie hilft Anlegern zu erkennen, ob das Unternehmen eine attraktive Verzinsung auf das eingesetzte Eigenkapital erwirtschaftet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalrendite spricht für ein starkes, effizientes Geschäftsmodell.
- Besonders interessant ist sie bei kapitalintensiven Firmen oder solchen mit hoher Eigenkapitalquote.
- Wichtig: Ein sehr hoher ROE kann auch auf hohe Schulden hinweisen – daher sollte sie immer im Kontext mit der Eigenkapitalquote betrachtet werden.
📘 Return on Capital Employed (ROCE)
📈 Was ist das?
ROCE misst die Gesamtrentabilität eines Unternehmens – also wie effizient es das eingesetzte Kapital (Eigen- und Fremdkapital) zur Gewinnerzielung nutzt.
🧮 Wie wird es berechnet?
Das eingesetzte Kapital ist das gesamte betriebsnotwendige Kapital, unabhängig von der Finanzierungsquelle.
🏛️ Wofür ist es wichtig?
ROCE eignet sich besonders gut für den Vergleich unterschiedlich finanzierter Unternehmen. Es zeigt, wie effektiv ein Unternehmen Kapital investiert – unabhängig von der Kapitalstruktur.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROCE zeigt, dass ein Unternehmen sein Kapital effizient einsetzt – unabhängig davon, ob es durch Eigen- oder Fremdkapital finanziert ist.
- Je höher der ROCE im Vergleich zu ähnlichen Unternehmen, desto mehr Wert schafft das Unternehmen mit seinem investierten Kapital.
- Besonders wichtig ist der ROCE bei Firmen mit hohen Investitionen – z. B. in Industrie, Energie oder Infrastruktur.
📘 Return on Invested Capital (ROIC)
📈 Was ist das?
ROIC zeigt, wie effizient ein Unternehmen das Kapital investiert, das langfristig im operativen Geschäft gebunden ist – unabhängig davon, ob es aus Eigen- oder Fremdkapital stammt.
🧮 Wie wird es berechnet?
- NOPAT = „Net Operating Profit After Taxes“
- Investiertes Kapital = operatives Vermögen abzüglich nicht-verzinster Schulden
🏛️ Wofür ist es wichtig?
ROIC ist eine der präzisesten Kennzahlen zur Bewertung der Kapitalrendite – besonders im Vergleich zur Eigenkapitalrendite, weil es Verzerrungen durch Schulden vermeidet. Er zeigt, ob ein Unternehmen Mehrwert für alle Kapitalgeber schafft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROIC zeigt, wie gut ein Unternehmen mit dem tatsächlich investierten (betriebsnotwendigen) Kapital wirtschaftet.
- Im Unterschied zu ROCE wird nur Kapital betrachtet, das wirklich zur Finanzierung operativer Aktivitäten dient – und verzinst werden muss.
- Besonders hilfreich, um die Kapitalrendite von Unternehmen mit viel „überschüssigem“ Kapital oder zinsfreien Verbindlichkeiten realistisch zu vergleichen.
📘 Verschuldungsgrad (Leverage Ratio)
📈 Was ist das?
Der Verschuldungsgrad zeigt, wie stark ein Unternehmen durch verzinsliche Schulden (z. B. Kredite und Anleihen) im Verhältnis zum Eigenkapital finanziert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Kennzahl hilft, das finanzielle Risiko und die Abhängigkeit von Fremdkapital zu beurteilen. Ein hoher Verschuldungsgrad kann die Eigenkapitalrendite steigern – birgt aber auch erhöhte Risiken bei Zinsanstiegen oder Liquiditätsengpässen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Verschuldungsgrad steht für finanzielle Stabilität und Unabhängigkeit.
- Ein hoher Wert kann auf erhöhte Risiken hinweisen – insbesondere bei schwankenden Zinsen oder konjunkturellen Schwächen.
- Wichtig: Immer im Kontext zur Branche und Kapitalintensität bewerten.
📘 SBC | in % Umsatz
📈 Was ist das?
SBC (Stock-Based Compensation) bezeichnet die aktienbasierte Vergütung, die ein Unternehmen seinen Mitarbeitern und Führungskräften gewährt. Der Prozentanteil zeigt, wie hoch die SBC im Verhältnis zum Umsatz ist.
🧮 Wie wird es berechnet?
SBC in % Umsatz = (SBC ÷ Umsatz) × 100
🏛️ Wofür ist es wichtig?
Aktienbasierte Vergütung ist für Aktionäre ein realer Kostenfaktor. Sie erhöht die Aktienanzahl und verwässert damit die bestehenden Anteile. Der Anteil am Umsatz zeigt, wie stark ein Unternehmen auf dieses Mittel setzt und wie viel der Wertschöpfung an Mitarbeiter statt an Aktionäre fließt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Wert ist grundsätzlich positiv: Die aktienbasierte Vergütung fällt im Verhältnis zum Umsatz gering aus.
- Ein hoher Wert kann dagegen auf eine stärkere Abhängigkeit von aktienbasierter Vergütung und ein höheres potenzielles Verwässerungsrisiko hindeuten. Entscheidend ist dabei auch, ob das Unternehmen die Verwässerung durch Aktienrückkäufe ausgleicht.
📘 SBC in % FCF
📈 Was ist das?
SBC (Stock-Based Compensation) bezeichnet die aktienbasierte Vergütung, die ein Unternehmen seinen Mitarbeitern und Führungskräften gewährt. Der Prozentanteil zeigt, wie hoch die SBC im Verhältnis zum Free Cashflow (FCF) ist.
🧮 Wie wird es berechnet?
SBC in % FCF = (SBC ÷ Free Cashflow) × 100
🏛️ Wofür ist es wichtig?
Aktienbasierte Vergütung ist für Aktionäre ein realer Kostenfaktor. Sie erhöht die Aktienanzahl und verwässert damit die bestehenden Anteile. Der Anteil am freien Cashflow zeigt, wie groß die SBC im Verhältnis zur vom Unternehmen erwirtschafteten Cash-Generierung ist. Da SBC nicht zahlungswirksam ist, wird sie bei der Berechnung des FCF typischerweise nicht als Cash-Abfluss berücksichtigt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Wert ist hier meist günstig. Die aktienbasierte Vergütung fällt im Verhältnis zur Cash-Erzeugung gering aus.
- Ein hoher Wert bedeutet, dass ein großer Teil des ausgewiesenen freien Cashflows durch nicht zahlungswirksame SBC gestützt wird.
- Je höher der Wert, desto stärker kann die SBC die tatsächliche wirtschaftliche Belastung für Aktionäre widerspiegeln.
📘 SBC-Wachstum 1J
📈 Was ist das?
Das SBC-Wachstum 1J zeigt, wie stark sich die aktienbasierte Vergütung (Stock-Based Compensation) eines Unternehmens im Vergleich zum Vorjahr verändert hat.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das SBC-Wachstum zeigt, ob die aktienbasierte Vergütung für Aktionäre zunehmend oder abnehmend relevant wird. Steigt die SBC deutlich, kann dadurch langfristig auch die Verwässerung der Aktionäre zunehmen. Gleichzeitig handelt es sich um einen nicht zahlungswirksamen Aufwand, der in der Gewinn- und Verlustrechnung das Ergebnis mindert, in der Kapitalflussrechnung jedoch wieder hinzugerechnet wird.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher positiver Wert ist meistens negativ, denn steigende SBC kann die Belastung für Aktionäre erhöhen, insbesondere durch mögliche Verwässerung.
- Entscheidend ist, ob die Entwicklung der SBC langfristig nachhaltig bleibt. Ein gewisses Maß an SBC ist bei vielen Wachstums- und Technologieunternehmen üblich.
📘 Aktienanzahl-Wachstum 1J
📈 Was ist das?
Das Wachstum der Aktienanzahl zeigt, wie stark sich die Zahl der ausstehenden Aktien innerhalb eines Jahres verändert hat.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Aktienanzahl bestimmt, auf wie viele Anteile sich Gewinn und Vermögen des Unternehmens verteilen. Sinkt die Anzahl der Aktien, steigt der relative Anteil bestehender Aktionäre. Steigt sie, werden bestehende Aktionäre verwässert. Die Kennzahl macht damit Verwässerung und Aktienrückkäufe direkt sichtbar.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein negativer Wert ist meist positiv, da die Zahl der ausstehenden Aktien zurückgeht.
- Ein positiver Wert deutet auf eine Verwässerung bestehender Aktionäre hin.
- Ein sinkender Wert ist nicht automatisch positiv: Entscheidend ist auch, zu welchem Preis und wie die Rückkäufe finanziert werden.
📘 Shareholder Yield
📈 Was ist das?
Der Shareholder Yield zeigt, wie viel Wert ein Unternehmen im Verhältnis zu seiner Marktkapitalisierung durch Dividenden, Aktienrückkäufe und Schuldenabbau für seine Aktionäre schafft. Damit geht die Kennzahl über die klassische Dividendenrendite hinaus.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Dividendenrendite allein zeigt nur einen Teil davon, wie ein Unternehmen sein Kapital zugunsten der Aktionäre einsetzt. Neben Dividenden können auch Aktienrückkäufe den Anteil bestehender Aktionäre am Unternehmen erhöhen. Ein Abbau der Verschuldung stärkt zusätzlich die finanzielle Position des Unternehmens. Der Shareholder Yield fasst diese drei Komponenten in einer Kennzahl zusammen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein höherer Wert bedeutet mehr Kapitalrückgabe bzw. einen stärkeren Schuldenabbau zugunsten der Aktionäre.
- Die Zusammensetzung ist wichtig: Dividenden, Rückkäufe und Schuldenabbau haben unterschiedliche Auswirkungen.
- Rückkäufe schaffen nur dann Wert, wenn die Aktien zu attraktiven Preisen zurückgekauft werden.
- Entscheidend ist auch, ob die Kapitalrückgaben und der Schuldenabbau nachhaltig finanziert werden.
📘 Umsatz
📈 Was ist das?
Der Umsatz zeigt, wie viel ein Unternehmen insgesamt mit seinen Produkten und Dienstleistungen verdient – also den Bruttoerlös vor Abzug von Kosten.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Umsatz ist eine der zentralen Kennzahlen zur Einschätzung der Unternehmensgröße, Marktstellung und Wachstumskraft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein wachsender Umsatz zeigt eine steigende Nachfrage und kann ein guter Frühindikator für Gewinnsteigerungen sein.
- Vergleiche von aktuellem und erwartetem Umsatz geben Hinweise auf das Marktumfeld und Analystenerwartungen.
- Wichtig: Starker Umsatz allein genügt nicht – auch Margen und Profitabilität zählen.
📘 EBITDA
📈 Was ist das?
EBITDA steht für „Earnings Before Interest, Taxes, Depreciation and Amortization“ – also Gewinn vor Zinsen, Steuern und Abschreibungen. Es zeigt das operative Ergebnis eines Unternehmens, bereinigt um bilanztechnische und finanzierungsbedingte Effekte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBITDA ist eine verbreitete Kennzahl zur Beurteilung der operativen Leistungsfähigkeit – insbesondere bei kapitalintensiven Unternehmen oder im internationalen Vergleich.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes oder wachsendes EBITDA spricht für starke operative Erträge – unabhängig von Bilanzierung oder Steuerlast.
- EBITDA ist besonders nützlich, um Unternehmen branchenübergreifend zu vergleichen.
- Wichtig: EBITDA ist keine offizielle Gewinnkennzahl – Abschreibungen und Finanzierungskosten werden ausgeklammert.
📘 EBIT
📈 Was ist das?
EBIT steht für „Earnings Before Interest and Taxes“ – also Gewinn vor Zinsen und Steuern. Es zeigt das operative Ergebnis eines Unternehmens nach Abschreibungen, aber vor Finanzierungs- und Steueraufwand.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBIT ist eine zentrale Kennzahl zur Beurteilung der Profitabilität aus dem Kerngeschäft – unabhängig von Kapitalstruktur oder Steuersystem.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes EBIT deutet auf ein profitables Kerngeschäft hin – vor Zinslasten oder steuerlichen Effekten.
- Es erlaubt objektivere Vergleiche zwischen Unternehmen mit unterschiedlicher Finanzierung.
- Im Vergleich mit EBITDA zeigt EBIT bereits den Einfluss von Abschreibungen auf das operative Ergebnis.
📘 Nettogewinn
📈 Was ist das?
Der Nettogewinn ist der verbleibende Jahresüberschuss (oder -fehlbetrag) eines Unternehmens – nach Abzug aller Kosten, Steuern, Zinsen und Abschreibungen
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Nettogewinn ist die zentrale Erfolgskennzahl – er zeigt, wie profitabel ein Unternehmen nach allen Kosten tatsächlich arbeitet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein steigender Nettogewinn zeigt, dass das Unternehmen effizient wirtschaftet – trotz aller Kosten.
- Die Entwicklung des Gewinns beeinflusst z. B. direkt das KGV und weitere Kennzahlen.
- Im Zeitverlauf lässt sich ablesen, wie stabil und profitabel ein Geschäftsmodell wirklich ist.
📘 Free Cashflow (FCF) | ex SBC
📈 Was ist das?
Der Free Cashflow gibt an, wie viel Bargeld tatsächlich übrig bleibt, nachdem ein Unternehmen seine Betriebsausgaben und Investitionsausgaben gedeckt hat. Der FCF ex SBC zieht zusätzlich die aktienbasierte Vergütung ab, um den Cashflow um den Effekt der nicht zahlungswirksamen SBC zu bereinigen.
🧮 Wie wird es berechnet?
Free Cashflow ex SBC = Operativer Cashflow − SBC − Investitionen in Sachanlagen (CAPEX)
🏛️ Wofür ist es wichtig?
Der FCF spiegelt die tatsächliche Finanzkraft eines Unternehmens wider – unabhängig von den bilanziellen Gewinnen. Er zeigt, wie viel Spielraum ein Unternehmen für Dividenden, Aktienrückkäufe oder den Schuldenabbau hat. Der FCF ex SBC zieht zusätzlich die aktienbasierte Vergütung ab und zeigt, wie hoch die Cash-Generierung nach Abzug der SBC ausfällt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow bedeutet, dass ein Unternehmen echte Finanzkraft besitzt – unabhängig vom bilanzierten Gewinn.
- Er ist oft die solideste Grundlage für nachhaltige Dividenden und Aktienrückkäufe.
- Sinkender FCF kann ein Warnsignal sein – auch wenn der Gewinn stabil aussieht.
📘 Umsatzwachstum
📈 Was ist das?
Das Umsatzwachstum zeigt, wie stark sich die Erlöse eines Unternehmens im Vergleich zum Vorjahr verändert haben – tatsächlich (TTM) und auf Prognosebasis (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (Umsatz erwartet ÷ Umsatz Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein wachsender Umsatz ist ein zentrales Signal für steigende Nachfrage, Geschäftsausweitung und Marktanteilsgewinne – besonders bei Wachstumsunternehmen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachstum ist der Motor langfristiger Wertsteigerung – besonders bei Technologie- und Wachstumsaktien.
- Wichtig ist nicht nur das aktuelle Wachstum, sondern auch dessen Nachhaltigkeit.
- Prognosen zeigen, ob Analysten weiteres Potenzial erwarten – oder eine Verlangsamung.
📘 EBITDA-Wachstum
📈 Was ist das?
Das EBITDA-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens vor Zinsen, Steuern und Abschreibungen im Vergleich zum Vorjahr gestiegen oder gesunken ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBITDA ÷ EBITDA Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein steigendes EBITDA ist ein Zeichen für verbesserte operative Ertragskraft – unabhängig von Finanzierungsstruktur oder Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Starkes EBITDA-Wachstum signalisiert operative Effizienz und Skalierung – besonders relevant in Wachstumsphasen.
- EBITDA-Wachstum ist ein Frühindikator für Margen- und Gewinnentwicklung – sollte aber stets im Zusammenhang mit Umsatz und EBIT betrachtet werden.
📘 EBIT Wachstum
📈 Was ist das?
Das EBIT-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens (nach Abschreibungen, aber vor Zinsen und Steuern) im Vergleich zum Vorjahr gewachsen ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBIT ÷ EBIT Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Das EBIT-Wachstum ist ein direkter Indikator für die wirtschaftliche Entwicklung des operativen Geschäfts – unter Berücksichtigung der Kapitalintensität (Abschreibungen).
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Steigendes EBIT signalisiert wachsende operative Rentabilität – auch unter Berücksichtigung von Abschreibungen.
- Das EBIT-Wachstum ist ein wichtiges Maß zur Beurteilung von Geschäftsmodellen mit hohen Investitionskosten.
- Im Zusammenspiel mit Umsatz- und EBITDA-Wachstum ergibt sich ein umfassendes Bild zur operativen Entwicklung.
📘 Nettogewinn-Wachstum
📈 Was ist das?
Das Nettogewinn-Wachstum zeigt, wie stark der Jahresüberschuss eines Unternehmens gegenüber dem Vorjahr gestiegen oder gesunken ist – sowohl tatsächlich (TTM) als auch auf Basis von Prognosen (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (erwarteter Nettogewinn ÷ Nettogewinn Vorjahr − 1) × 100
Der erwartete Wert basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Der Gewinn ist die entscheidende Ergebnisgröße für ein Unternehmen. Ein wachsender Nettogewinn deutet auf steigende Effizienz, stabile Kostenkontrolle und nachhaltige Ertragskraft hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachsender Nettogewinn stärkt die Bewertung, Dividendenfähigkeit und Kursfantasie.
- Stagnierender oder rückläufiger Gewinn trotz Umsatzwachstum kann auf Margendruck hinweisen.
📘 Free Cashflow-Wachstum
📈 Was ist das?
Das Free-Cashflow-Wachstum zeigt, wie sich der freie Mittelzufluss eines Unternehmens im Vergleich zum Vorjahr verändert hat – also der Betrag, der nach allen operativen Ausgaben und Investitionen übrig bleibt.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Free Cashflow ist der echte, verfügbare Geldzufluss. Wachstum in diesem Bereich ist ein Zeichen für finanzielle Stärke und steigende Flexibilität bei Dividenden, Rückkäufen oder Investitionen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Sinkender Free Cashflow kann auf steigende Investitionen, höhere Kosten oder stagnierende operative Erträge hindeuten.
- Besonders bei Dividendenwerten ist das FCF-Wachstum wichtig – denn Dividenden werden letztlich aus dem verfügbaren Cash gezahlt.
- Ein negativer Trend sollte genauer analysiert werden – er ist nicht zwangsläufig schlecht, aber potenziell ein Warnsignal.
📘 Bruttomarge
📈 Was ist das?
Die Bruttomarge zeigt, wie viel vom Umsatz nach Abzug der direkten Herstellungskosten (Material, Produktion) als Bruttogewinn übrig bleibt – also der „Rohgewinn“ eines Unternehmens.
🧮 Wie wird es berechnet?
Auch: Bruttomarge = Bruttogewinn ÷ Umsatz × 100
🏛️ Wofür ist es wichtig?
Die Bruttomarge gibt Aufschluss über die Profitabilität eines Produkts oder Geschäftsmodells vor Fixkosten, Steuern und Zinsen. Sie zeigt, wie effizient ein Unternehmen produzieren oder einkaufen kann.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Bruttomarge deutet auf starke Preissetzungsmacht und effiziente Herstellung hin.
- Sinkende Bruttomargen können auf Kostensteigerungen oder Preisdruck hindeuten.
- Besonders im Vergleich zu Wettbewerbern liefert die Bruttomarge wertvolle Einblicke in die Geschäftsqualität.
📘 EBITDA-Marge
📈 Was ist das?
Die EBITDA-Marge zeigt, wie viel vom Umsatz als operativer Gewinn vor Zinsen, Steuern und Abschreibungen (EBITDA) übrig bleibt. Sie misst die operative Effizienz – ohne Verzerrungen durch Finanzierung oder Buchwerte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBITDA-Marge hilft zu verstehen, wie viel operativer Gewinn ein Unternehmen aus jedem Euro Umsatz erzielt – unabhängig von Kapitalstruktur oder steuerlichem Umfeld.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBITDA-Marge zeigt starke operative Ertragskraft – unabhängig von Bilanzierungseffekten.
- Die Marge ermöglicht gute Vergleiche zwischen Unternehmen und Branchen.
- Ein stabiler oder wachsender Wert kann auf effiziente Kostenkontrolle und Skalierbarkeit hindeuten.
📘 EBIT-Marge
📈 Was ist das?
Die EBIT-Marge zeigt, wie viel Prozent des Umsatzes als operativer Gewinn nach Abschreibungen, aber vor Zinsen und Steuern übrig bleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBIT-Marge misst die operative Ertragskraft eines Unternehmens unter Berücksichtigung der Kapitalintensität (z. B. Maschinen, Anlagen). Sie eignet sich gut zum Vergleich von Geschäftsmodellen mit unterschiedlich hohen Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBIT-Marge zeigt, dass ein Unternehmen auch nach Abschreibungen effizient arbeitet.
- Sie ist besonders relevant in kapitalintensiven Branchen.
- Langfristig stabile oder steigende Margen sind ein Zeichen wirtschaftlicher Stärke und Preissetzungsmacht.
📘 Nettomarge
📈 Was ist das?
Die Nettomarge zeigt, wie viel vom Umsatz am Ende als „Reingewinn“ übrig bleibt – also nach Abzug aller Kosten, Zinsen, Steuern und Abschreibungen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Nettomarge gibt an, wie effizient ein Unternehmen über alle Stufen hinweg wirtschaftet. Sie zeigt, wie viel Gewinn tatsächlich je Euro Umsatz übrig bleibt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Nettomarge zeigt, dass ein Unternehmen nicht nur operativ stark ist, sondern auch seine Finanzierung und Steuerbelastung im Griff hat.
- Vergleiche mit Wettbewerbern geben Einblicke in die wirtschaftliche Qualität.
- Sinkende Nettomargen trotz Umsatzwachstum können ein Warnsignal sein – etwa für steigende Kosten oder sinkende Effizienz.
📘 Free-Cashflow-Marge | ex SBC
📈 Was ist das?
Die Free-Cashflow-Marge zeigt, wie viel Free Cashflow ein Unternehmen im Verhältnis zu seinem Umsatz erwirtschaftet. Der Free Cashflow entspricht vereinfacht dem operativen Cashflow abzüglich der Investitionsausgaben. Die Free-Cashflow-Marge ex SBC berücksichtigt zusätzlich aktienbasierte Vergütungen (Stock-Based Compensation, SBC). SBC verursacht zwar keinen direkten Cash-Abfluss, kann bestehende Aktionäre jedoch durch die Ausgabe zusätzlicher Aktien verwässern. Daher wird SBC bei dieser Kennzahl vom Free Cashflow abgezogen.
🧮 Wie wird es berechnet?
Free-Cashflow-Marge ex SBC = (Free Cashflow − SBC) ÷ Umsatz × 100
🏛️ Wofür ist es wichtig?
Die Free-Cashflow-Marge zeigt, wie effizient ein Unternehmen seinen Umsatz in Free Cashflow umwandelt. Ein hoher Free Cashflow kann dem Unternehmen finanziellen Spielraum für Dividenden, Aktienrückkäufe, Schuldentilgung oder weitere Investitionen geben. Die Variante ex SBC berücksichtigt zusätzlich die wirtschaftliche Belastung durch aktienbasierte Vergütungen und ermöglicht dadurch eine konservativere Betrachtung der Cash-Generierung aus Sicht der Aktionäre.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Free-Cashflow-Marge zeigt, dass ein Unternehmen einen hohen Anteil seines Umsatzes in Free Cashflow umwandelt.
- Das kann dem Unternehmen mehr finanziellen Spielraum für Dividenden, Aktienrückkäufe, Schuldentilgung oder Investitionen geben.
- Die Free-Cashflow-Marge ex SBC berücksichtigt zusätzlich die mögliche Verwässerung durch aktienbasierte Vergütungen.
- Besonders aussagekräftig ist die Entwicklung über mehrere Jahre. Sinkende Werte können beispielsweise auf höhere Investitionen, Veränderungen im Working Capital oder eine schwächere operative Entwicklung zurückzuführen sein.
📘 Ergebnis je Aktie (EPS)
📈 Was ist das?
Das Ergebnis je Aktie (EPS) zeigt, wie viel Gewinn auf eine einzelne Aktie entfällt – und ist eine der wichtigsten Kennzahlen zur Bewertung von Unternehmen.
🧮 Wie wird es berechnet?
Die verwässerte Aktienanzahl berücksichtigt auch potenzielle neue Aktien, etwa durch Optionen, Wandelanleihen oder andere Umtauschrechte.
🏛️ Wofür ist es wichtig?
EPS bildet die Basis für viele Bewertungskennzahlen wie KGV, PEG oder Payout Ratio. Es macht den Gewinn für Aktionäre vergleichbar – unabhängig von der Unternehmensgröße.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- EPS hilft, die Profitabilität pro Aktie zu erfassen – und ist besonders wichtig im Zeitvergleich oder im Vergleich mit Analystenschätzungen.
- Steigendes EPS kann ein Zeichen für stabiles Wachstum oder Aktienrückkäufe sein.
- Wichtig: Verwende verwässertes EPS für realistische Bewertungen – besonders bei stark aktienbasierten Vergütungssystemen.
📘 Free Cashflow je Aktie (FCF je Aktie)
📈 Was ist das?
Der Free Cashflow je Aktie zeigt, wie viel freier Mittelzufluss einem Unternehmen pro Aktie zur Verfügung steht – nach Investitionen, aber vor Dividenden oder Schuldentilgung.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der FCF je Aktie zeigt, wie viel liquide Mittel pro Aktie tatsächlich im Unternehmen verbleiben – wichtig für Dividenden, Aktienrückkäufe oder Schuldentilgung. Im Gegensatz zum Gewinn ist er schwerer manipulierbar und daher besonders aussagekräftig.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow je Aktie ist ein Zeichen für hohe finanzielle Flexibilität.
- Er zeigt, wie viel Kapital ein Unternehmen effektiv einsetzen oder ausschütten kann.
- Besonders relevant für dividendenstarke Unternehmen oder solche mit starker Kapitalrendite.
📘 Short Interest
📈 Was ist das?
Short Interest zeigt, wie viele Aktien eines Unternehmens aktuell leerverkauft wurden – also von Investoren geliehen und verkauft, in der Erwartung fallender Kurse.
🧮 Wie wird es berechnet?
Der Wert zeigt den Anteil der Aktien, der aktuell auf fallende Kurse spekuliert wird.
🏛️ Wofür ist es wichtig?
Short Interest dient als Stimmungsindikator: Ein hoher Wert deutet auf Skepsis oder negative Erwartungen gegenüber dem Unternehmen hin – kann aber auch zu einem „Short Squeeze“ führen, wenn der Kurs plötzlich steigt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Short Interest deutet auf Vertrauen in das Unternehmen hin.
- Ein hoher Wert kann ein Warnsignal sein – oder eine Chance, wenn sich die Stimmung dreht.
- Besonders spannend in volatilen Märkten oder vor wichtigen Quartalszahlen.
📘 Employees
📈 Was ist das?
Die Mitarbeiteranzahl zeigt, wie viele Personen ein Unternehmen weltweit beschäftigt – ein Indikator für Größe, Struktur und Geschäftsmodell.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft bei der Einschätzung von Skaleneffekten, Effizienz und Personalkosten. Zusammen mit Umsatz und Gewinn lassen sich Kennzahlen wie Produktivität je Mitarbeiter ableiten.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Viele Mitarbeiter bedeuten große operative Komplexität – aber auch hohes Umsatzpotenzial.
- Produktivität je Mitarbeiter ist ein wichtiger Indikator für Effizienz.
- Besonders spannend bei stark wachsenden Tech- oder Industrieunternehmen.
📘 Umsatz je Mitarbeiter
📈 Was ist das?
Der Umsatz je Mitarbeiter zeigt, wie viel Erlös ein Unternehmen durchschnittlich pro Beschäftigtem erwirtschaftet – eine Kennzahl für Effizienz und Produktivität.
🧮 Wie wird es berechnet?
Die Mitarbeiterzahl stammt in der Regel aus dem letzten verfügbaren Jahresbericht.
🏛️ Wofür ist es wichtig?
Diese Kennzahl hilft, Geschäftsmodelle zu vergleichen – insbesondere zwischen arbeitsintensiven und technologiegetriebenen Unternehmen. Ein hoher Wert deutet auf Automatisierung, Effizienz oder hohen Wertschöpfungsanteil hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Umsatz je Mitarbeiter spricht für ein skalierbares und margenstarkes Geschäftsmodell.
- Ein niedriger Wert kann auf arbeitsintensive Prozesse oder geringere Wertschöpfung hinweisen.
- Besonders hilfreich beim Vergleich von Tech- vs. Industrieunternehmen.
Figma Aktie Analyse
Analystenmeinungen
18 Analysten haben eine Figma Prognose abgegeben:
Analystenmeinungen
18 Analysten haben eine Figma Prognose abgegeben:
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Figma — Goldman Sachs Communacopia + Technology Conference 2026
1. Question Answer
Okay. Fantastic. We will go ahead and kick it off with Figma. Can we get the doors closed, please? Delighted to be on stage with [ Fiona Zhang ], my colleague and Dylan Field, CEO and Founder of Figma. Thank you for your time today.
Thank you for having me.
Dylan, I want to ask you a little bit about the product road map over the next 12 months. We came back from the Figma conference and the number of products that you're announcing in a very short amount of time has gone up. At the same time, 1 of the dynamics that we've talked about on the earnings call is this idea that customers are in a period of experimentation. So talk a little bit about what the vision for how Figma up levels into that period of innovation over the next 12 months and some of the things that you're looking at to gauge success?
Absolutely. I think maybe taking a step back, it's this wild time and 1 that we have wanted to see come true for so long. The amount of software that people are building the amount of creativity that folks are exploring, it's expanding so fast, it feels exponential. And then you look at adoption, and it's kind of flat overall. So not everything is getting actually adopted. Not everything is getting developed fully. And the attention economy at the end of the day is like quite limited for software, whether it's an enterprise, consumer, for marketing across all areas where people are using software as part of the business. The fight for attention is constant.
And so when you look back at the launches we did at Config, a lot of that was around expression. How do you get the best ideas out there in a way that you can still shape but also with the benefit of AI. And so went for things like motion and expressive shaders, the ability to create your own tools in Figma and more.
And now I think as we look across our platform, the first thing that we always have to remind ourselves of is design and designers are core, and we must always cater to their needs and make sure that they are the first folks that we take care of on the platform. I think that there's tons of opportunity outside of design as well. And as we look at it and look at the improvements that we're seeing with LLMs right now, I mean, it's pretty mind-boggling, how fast they're improving. And I think our core strategy remains the same, which is basically we see code as being increasingly commoditized, as it becomes more commoditized, I don't believe that the layer on top of that, they have [ abstraction ] of text, I think it's visual. I think that's what most people, including designers, want is to actually interact with a visual medium to go change and to pick up and really reflect their own point of view in the design in the medium. And as we do that, I think that, that will be increasingly the starting point from which you then go make APR from which you ship code and measure it. And if we can do that, I think it really enables us to open up code in the canvas alongside all sorts of other mediums because then the day code is just like an implementation detail. It's not the -- what it's not like what people are going for. And so to the degree we can do that fully, I think it expands the platform an opportunity quite a lot and puts us more in the token flow overall.
It leads nicely into a question on the evolution of user interface. One of the [ bare ] cases we've heard is, we can envision a world where knowledge workers have essentially some sort of central pane of glass with pumped bar and they're operating all of these different applications in the background, off of the pump bar rather than actually interacting with any specific app. Or you have agents and they are the ones actually doing the heavy lifting. They don't need a user interface. Maybe give us the pushback to that more bearish view of UI evolution?
Well, I don't think it's entirely bearish, first of all. But I would say that overall, like the core -- 1 of the core thesis of Figma is alongside prompting to get started and to get something out on to the canvas that you can like start thinking about and respond to because I'm sure all of you feel this new or staring at a blank canvas, a blank page, that is the hardest thing to be able to catalyze yourself into going [ crane ], editing, iterating from there. And to get some on the canvas is incredible. To able to do these tests that are pretty menial might take hours and automate them away is so helpful.
But yes, to the degree that we're able to make it so people can get within [ each other's ] head onto the canvas and translate that and achieve with their hands of direct [ manipulation ] and also not just be building in 1 direction, whatever they happen to get from the agent, but actually building the right thing, which requires exploration. It requires divergence. And I think that the canvas is very useful here, it's a bird's eye view to actually have a sense of all the things that are going on, [ zero in ] on the thing that matters. That is ultimately where I see has been a very important step that a lot of folks are reporting to us as missing right now. We've gone from a place where designers and design teams inherently diverged to many folks trying to adopt AI workflows and process losing what made them designers in the first place and then trying to get back to it and figuring out, okay, how do we solve this? One of the things that we also launched in Config, sorry, announced in Config, and will be launched soon is Code Layers. And this isn't a way to just put a code on the canvas in that way across all these mediums, you can also see code and have a full function prototype that you can consider alongside other options.
Fantastic. Okay. Let me ask you 1 more core Figma IP question before we start talking about competition. One of the things that's always [ shot out ] to us on the Figma back end is the way that you solved multiplayer. So multiple folks in the room can orchestrate across 1 canvas and the changes sort of sync seamlessly. That seems like a pretty important piece of IP for how agents work because agents also have to sync. So walk us through what that could look like? Can you use your core IP on multiplayer, essentially the gaming engine that you have? Can you extend that to agents?
Yes. I mean, first of all, we agree. We think it's a big opportunity to bring not just humans but also agents into the canvas together. With the Figma agent you're starting to see the innings of that, more to come. And that's 1 of the things I'm most excited about right now is how we can get the agent in Figma design to be maximally useful, high quality, but also really fast. I think the speed, the cost and the quality, those are 3 parts of it that all matter.
I wouldn't say it's the only thing that matters, though, is getting agents and humans working alongside each other. I also think that anything you can do to be able to be in the data loop of the customer creates context then creates capability for the customer too. And I think that is something that will increasingly be seen as a core mode of the business and a big part of the way that we better serve customers as well.
Let's talk a little bit more about competition. So the tools from Frontier Labs or AI native startups are no longer just about generating code anymore, but they're generating more complete products. So the Frontier Lab models continue to innovate and improve at their current pace. Where do you see the swim lanes are converging with Figma potentially?
Yes. I think that it's been super impressive how the Frontier models overall are improving. I mean, if you all are playing with Astra, for example, which just came out, I mean, what it can do with math, what it can do on the coding side and the improvements we're seeing overall there are very strong.
I would say for design, it feels they get incremental. There's always a sort of psychosis we will go through a few days after a model release where it's like the best things bubble to the top of the algo feed. And then you're like, "Oh, but I can do the thing," and then you try to do the thing, it doesn't quite work. And our only [ valves ] like it is progress. It's incremental on design, but overall, this is still in the realm of -- I think the visuals are not quite there, let alone the experiential details, UX providing and actually understanding larger context. And adhering to a design system, especially as design systems involve more and more complexities. And so I think that, that's been both our challenge and our opportunity is how do we take models frontier, proprietary and make it that we're able to actually use them to make the lives of designers better and the workflows of designers better as well as everyone they're working with.
And so that's a huge area of our focus when it comes to Figma agent is making it so that we are able to provide truly valuable use cases there.
With these Frontier Labs and AI native start-ups, how do you balance openness and partnership while maintaining strategic differentiation from them?
Yes. I mean our MCP, I think, is a good example of this, where with MCP, we've tried to make sure that you can go from Figma designs that exist in the canvas, click 1, pull in the MCP, through MCP into your coding agent, and go build it. And I think what's been also really exciting is to see the growth overall of the way that these are now writing back to Figma. And overall, we're seeing just a ton of people, which is growing quarter-over-quarter in significant ways, writing back with our [ used ] Figma tool call to the canvas, which I think just shows how the Canvas remains the center of work even as models get better and better. And I think that as Figma agent increases quality and speed gets better, too, we'll see more and more of that work happening in Figma directly, rather than going out to the Figma -- to the coding agent in a terminal or an ID where we've heard repeatedly from our customers. It's not where they want to work. It's not where they want to live and instead starting in your design tool.
You talked about the importance of context. And then 1 of the major debates we hear is where and who owns the proprietary data moats. What you need context does Figma accumulate across the product development life cycle? And why is that context so difficult for a competitor to replicate?
Yes. I think that going back quite a ways, whether or not a company wants us to use it, we have incredible context on the designs, the commentary and feedback, workflow, design systems of a customer. And this can both be helpful for our first-party model training. And in the future, as we branch out and are able to work with our customers more to enable them to fully use the contact and Figma design, they already can use the context they have outside of Figma design, but we want to make sure they can use it more first-party as well. That, I think, will be increasing, like I said, the data moat that matters. And all of that is workflow data that can really impact the way you work and expand it so that more people in your organization are able to use Figma and go create, whether it's continuing ideas to a software project or it's making it that you're able to express different branding marketing you want to do. These are all opportunities. I think more people in the organization as AI gets people to go more generalist will want to contribute to, and we're already seeing lots of signs of that.
Dylan, maybe just make this example a little bit more tangible. So let's say, we're a large financial institution. We have all of our branding content in-house. We have all of our data assets stored in Figma. Explain to us the difference between using something like the Figma agent to be able to start a new mobile app versus plugging in 1 of the third-party coding tools, 1 of the third-party LLMs, giving it access to that data set and saying, here are all the data assets you need go build us the mobile app?
Sure. I think that in the future, you'll be asking about where do you want your data to live. And you'll also be trying to figure out, okay, what are the different ways to ensure correctness of our assets, whether it's on brand and marketing or it's in software. Actually adhering to these design systems, brand guidelines is something that everyone cares about and a few are able to do with coding agents of anyone. And so it's a very big effort to get there, but 1 that we believe if we can enable customers to be able to define that, it will really help them.
Explain that a little bit more. So could I potentially give the coding agent, let's say, it's Claude, some sort of style guide or design guide that we've written in-house, maybe we even leverage Figma to do it. And then it goes off and sticks to the style guide and all the data still lives within the financial institution. Is that architecture something that would risk to Figma?
Well, right now, what we're seeing overall is even as these agents are improving, adherence, strict adherence to these guidelines is not a given. Hallucination is a huge issue as well as adhering to things in the wrong context. And so it's an easy thing to say. And I'm speaking as someone who said it before, and a harder thing to actually go make happen. And so I think that is 1 component of it. And I also think that there's many others in terms of the workflows that customers do and how we can make them truly actionable and make it so that the system is learning from them all the time.
So how did you then solve the same hallucination and commercial safety challenges within your own agent?
Well, we continue to [ hill climb ] on it, to be perfectly frank. I think that it's something that's been a focus of ours for quite a long time, and we're getting better and better. But I wouldn't say it's universally solved at this point. And I don't think it can be without the customer's help. And so that's typically where you fall down is if a customer -- a large financial institution, for example, were to say, okay, here is a set of written principles, it's [ actually ] not enough. You need to have positive and negative cases of what you want to see.
I think coming back to product a little bit. You've mentioned that AI has lowered the floor, but have yet to [ weigh ] the ceiling. If you look across your product road map in the next 12 to 24 months, what has the greatest potential in your mind to raise that ceiling?
I think our users, it's the case that people are able to do this incredible work overall with AI. But at the end of the day, every trope that gets created, that's at the center of the distribution is cliche after a very short amount of time. And so in order to actually go push that distribution in the first place, it requires cleverness, it requires a point of view and a reason why you're trying to go do something different. But if you don't, then you are out of luck, I think, because people just don't have the attention to go see the thing that's cliche over and over again. And they dismissed it actually as AI slop right away. I don't know if anyone in this room has the same reaction I do when they see [ writing the head ] like the AI cliche in it. It's not -- it's this, not that, for example, or you're absolutely correct. You can go on and on. But I think it's like kind of wild, I mean I stopped using em dashes for a while. Should I have? I like em dashes.
I like them too.
Yes, they're good.
They're grammatically correct.
But then I see people using em dash, and I'm like, slop. It's like you have this knee-jerk reaction. So I feel like there's plenty of AI tropes that are good in isolation, but then you don't want people to think you're just like generating something and putting out there. Is that dynamic to point out.
Wait, so what's the design equivalent of the em dash? How do you know when...
Gosh, I mean so many examples. It's also never [ evolving set ] too, like the most recent 1 is just quite a bunch of layouts, the very blocky designs, having, I think, actually, as amazing as 3D is, the abilities with the models to create with 3D now will rise -- lead to a rise of a lot of people doing stuff with 3D, and then there'll be like a knee-jerk, was that AI? Was it not? And I see some overuse there, a lot of [ beige ] recently. Before it was a purple gradient now its beige. So we're transforming.
Let me ask you on this topic. So there is a view that AI has been really good at coding for back-end architectures and engineering. But the issue of the limitation with front-end is it requires human judgment. So 1 could hypothesize that the front-end engineers that actually touch human design are more differentiated, more proprietary, more valuable than the back-end engineers where they don't touch human design. They're sort of isolated, does it work, does it not work, its their [ bible ]. I'm curious to your thoughts on that. Do you think that there will be an LLM curve, which then over time embeds judgment and human taste and preferences?
Well, I mean, the whole definitionally like communicate some preferences is not 1 thing, right? So I would maybe reject that hypothesis based on that definition alone contradictory. But also, I think the case that on the back end, I wouldn't say, at least in my experience, that I used to like throw [ it all over ] and then fine. It does still require human taste and judgment. If you want to build with modularity encapsulation, like good architecture and mines that's maintainable over the long term, [ same with ] front-end engineering, but especially design, where you're trying to actually make -- you can refresh an engineering system or code on the back-end faster than you can refresh a visual design. I don't know if any of you have tried to redesign, but everyone is always angry. At least, that's what happens at Figma. We have a very [indiscernible] user base. And so you have like an amount of time that you can change something in a huge way for users. And the bigger you are, the bigger your audience, the more you want to be very certain when you do.
Was there anything at Config that you announced or launched this year that has exceeded expectations from your user base?
I mean the thing that comes to mind first is the thing that we announced and did not launch yet, it's Code Layers. I mean, everyone saw that, I want it now. And so we've been trying to make sure that the quality is so high, that we're feeling really proud of it, and we're also seeing the usage internally. Now we are getting closer to that, which is great. And it's a pretty awesome experience because the Code Layers, you can have it, be that on the canvas, you have the full working prototype or many working prototypes prompted with agent, if you like. And then you can go right into design, directly manipulate, change what you want, reconcile back and it all is like working scratch pad that you can use in 1 place.
Is there anything in Figma, if you were to pinpoint, that can help elevate designers taste and judgment in a way that can make their front end better?
Well, I think that beyond just the core principles of the canvas with exploration and divergence and trying to get it that you're able to go through that workflow, which if you're an ID, it's an inherently linear workflow. The canvas is exploratory by default. It's just people gravitate towards exploring with that medium. I do believe a lot of this as we talked about earlier, with design systems, with adherence to not only design systems, but also brand and visual guidelines and style. Those are things that are the rails, if you will, for organizations that want to go design at scale. If you don't define them properly, then you just will -- you should expect to have divergence. And then it's kind of like the typical brand metaphor people might use or close. If you go outside and people see you wearing like a really goofy outfit, that's not typically you. They're kind of wondering like, oh, what happened? And I think there's different kind of close or different context, brand is 1 or [ priority lines ] and another, but they want to all work together to be something that feels similar enough. And your personality is being expressed some how to the user or to your friends. And I think that the ways that some companies could potentially end up going is if you have a lot of divergence, which no one wants, but it's easy to accomplish if you don't pay attention to it, then you end up kind of speaking to different languages to your users. And that's something that I think everyone is trying to get their arms around, but it's a very hard task.
Dylan, every quarter since the IPO, we asked Praveer 5 different gross margin questions. And does the sense that we're getting is, look, the reason that you can't be more specific about gross margins over the next 6 months is because of things like the canvas layers product where you don't know exactly what usage of monetization is going to look like. So maybe as a level setting point, talk to us about Figma Make. Figma Make, at least from what we can see from the outside in, you all had an incredible effort to improve that quality of the product to benchmark against competitors like Lovable and Bolt and you came from behind and the quality of the product got a lot better. You then turned on monetization and usage went up and it was incredible. And then customers sort of took a step back and said, "Oh, to see such thing is getting a little bit expensive. It's sort of coincided with the same period of time where we went from token maxing to actually thinking about value." And Figma make monetization seem to sort of do a little bit of umbrella shape in the quarter. My longer term -- my shorter way of asking the question is, what did you learn from Figma Make in terms of monetization?
Well, I think, first of all, it's odd thing where you talk with customers, and they're not always quoting price as the reason that they're not adopting, when you find people aren't adopting. And so at the same time, you have to be asking the back of your head, is it price? And that's an example of sort of 1 part of the thing in, of course, there's more, that went into decreasing the cost of credits recently. And we decreased them quite a bit in some cases, half, the cost is what it costs now. And so I'm really excited about just like what the industry has been seeing here without coming to [ specifics ] that we haven't shared yet. But in general, as prices go down for this stuff, then you see usage increase. And I think that Figma Make is not just about pricing packaging that you learn from. There's a ton that goes into actually building these products in the right way. And I think it's not yet appreciated that Figma Make is Code Layers. It's the same thing. It's just in a different context.
Okay. This is really interesting. So most investors when they hear that we cut the credits by half, we'll say, well, 1 of 2 things has to happen. It's great that usage is going up because cost has come down. But either Figma's cost of providing each of those credits also has to get cut in half or you have a gross margin problem. How do you respond to that?
Well, first of all, I think that we've already seen year-over-year how the cost of tokens in the frontier models is decreasing significantly. So sometimes in order of magnitude of way. And secondly, there is -- it's 2 things at work. One is there's a lot of ways to cut cost as long as you're not also cutting quality when it comes to serving users. On the other hand, and I think this should be the primary objective for us and likely for most of their companies and speak with right now, the opportunity is to drive volume. And I think it's much more important if you're going to stack rank the 2 right now to, first of all, raise the amount of volume flowing through the systems. Secondly, to figure out how you [ sell ] most efficiently.
Yes. Okay. And so...
That speaks to our priorities.
Absolutely. I hear you on the cost of tokens from the frontier model have come down. What are the levers do you have in place at Figma to keep the quality of the tool while also being able to deliver the new pricing model?
Well, the corollary point of the incremental progress that I mentioned in terms of frontier models is that if you look at the models from 2 months ago, 6 months ago, they are not lagging by that much when it comes to design and the ability is to do front-end work. And so I do think that coding as a market, not all saturated. But when it comes to like the abilities of code, of design, we will see like how much model improvement we get to on the frontier. Partially because as you get to like large and [ artery ] factors, that's probably where we'll see progress going forward on the coding side. And looking back on the design side, we haven't seen as much incremental improvement -- beyond incremental improvement so far. But I do think that there's a lot more you can get a boost on the areas of design overall. And partly, I think the trade is 1 of -- when you are optimizing a model and post-trading. If you are optimizing for code, it actually makes the writing worse. It makes a lot of other things worse, too. And these are all sort of -- there's some trade-offs there in terms of what you're trying to optimize for overall, which are -- they changed as you scale up models, but they are still there.
So what is the feedback been? What have you observed since you took the credit pricing down?
Unfortunately, not much to share today. But tune in next earnings, you all. Sorry.
No, no, I get it. And just to make sure we understand this correctly, the reason that, that was the right strategic decision from Figma was in response to a customer saying that pricing was too expensive. It sounds like it was more than that?
Well, I mean, first of all, you could define anything you want to find and user feedback always at scale. But I would say that at the end of the day, you also have to look at it, and just go, okay, would I be a buyer at this price point or not? And if it's too high, then you can just have like an honest reaction to that, too. So I think we all like did the gut check in varying customer feedback and went, this feels a bit too high, and it's most important to get the usage of the system and the volume growing.
You mentioned 1 of the main reasons when people are not adopting Make is not necessarily price. So what are the biggest kind of bottlenecks that you're seeing from your customers?
I think that there's -- for a while, it was quality. And we've since, I think, improved the quality to a place where, I mean, I'm actually loving Make now and I'm using it for a ton of use cases, both internally at Figma as well as at home. And I mean, it's incredible what I can do with a single prompt and also the aesthetic that you get, and it will get better over time. But really important is to be able to bring all that knowledge and context you have in Figma, to not just Make but also Code Layers, to agent and make it so that all these systems work together in parallel.
One of the bare cases we hear that as AI is democratizing design, something that is democratized for the portions of the professional workflow and becomes less valuable. So longer term, where do you see the role of a professional designer evolving? And kind of share with us what you're seeing with your customer base today?
Well, I think that the workflow overall is where we've seen the most divergence. Everyone's kind of scrambling and trying to figure out how do I work in AI world. This is across all disciplines. But especially with design, where it was a very linear workflow for a while, that's something that people have really been trying to figure out and looking to us for answers. And we're still looking at how we work, how the world works. So I think 1 thing that's becoming clear is we're seeing a lot more of desire to prototype upfront to get past that blank page problem, but then refine overall. And as you refine to really iterate ideate, think through the problem, both in design and code across mediums and then from there, go build. And so if I was going to abstract it out, that might be some of the clear sign posts. Along the way, you might be making decks. You might be brainstorming. You might be creating visual assets. Like there's so much that is embedded in that workflow, but you kind of go in and out of it. And it's really important to be able to have these clear ways to hand off work and also to acknowledge the power of code at the start of the process.
Fantastic. I think we can leave it here. Please join me in thanking Dylan for his time. Dylan, thank you.
Appreciate you having me.
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Figma — Goldman Sachs Communacopia + Technology Conference 2026
Figma setzt die Canvas als zentralen Hub für KI‑Agenten und Code‑Prototypen; Code Layers, Figma Agent und Preisänderungen bei Make stehen im Fokus.
🎯 Kernbotschaft
- Kerngedanke: Figma will die Canvas zum zentralen Arbeits‑ und Integrationslayer für Design und KI machen: Designer bleiben die Priorität, KI‑Agenten und Large Language Models (LLMs) sollen Einstieg, Geschwindigkeit und Prototyping liefern, während Code als Implementierungsdetail behandelt wird.
🚀 Strategische Highlights
- Code Layers: Kernprodukt angekündigt auf Config; zeigt laufende Prototypen/Code direkt auf der Canvas, soll Design↔Code‑Loop vereinfachen.
- Figma Agent & Multiplayer: Agenten werden zusammen mit menschlichen Nutzer:innen im selben Canvas arbeiten; Multiplayer‑Sync‑IP soll auch Agenten unterstützen.
- Datenmoat & Partner: Figma betont Workflow‑ und Designkontext als proprietäre Datenbasis; Offenheit gegenüber Frontier‑Modellen, aber Differenzierung durch Integration und Schreib‑Zurück‑Funktionen in die Canvas.
🔍 Neue Informationen
- Produktfokus: Konkrete Demo‑Priorität für Code Layers und Agent‑Integration; Code Layers noch nicht allgemein verfügbar, hohe interne Nachfrage.
- Preispolitik: Kreditkosten für Figma Make wurden deutlich gesenkt (teilweise ~50%), Ergebniskennzahlen zur Nutzungsänderung werden erst im nächsten Quartal erwartet.
❓ Fragen der Analysten
- Monetarisierung: Analysten haken auf Auswirkung der Kreditpreissenkung auf Umsatz und Bruttomarge; Management verweist auf sinkende Tokenkosten und Volumenfokus.
- Halluzination & Safety: Wie werden Agenten in regulierten Umgebungen (z. B. Banken) korrekt und sicher betreibbar gemacht? Figma sieht es als fortlaufende Aufgabe und betont Kunden‑Mitwirkung.
- Wettbewerb: Grenze zu Frontier‑Labs und AI‑Startups: Modelle verbessern sich, aber Figma glaubt, dass visuelle/erlebnisbezogene Komplexität und Design‑Systeme schwer zu ersetzen sind.
⚡ Bottom Line
- Relevanz: Produktstrategisch positioniert sich Figma als Plattform für KI‑gestützte Design‑Workflows mit starkem Fokus auf Integration und Datenkontext – potenziell hoher Nutzungshebel. Kurzfristig bleiben Monetarisierungseffekte, Bruttomargen und die technische Lösung von Halluzinationen Unsicherheitsfaktoren; der Wert der Daten‑ und Workflow‑Moat könnte langfristig Wettbewerbsvorteile sichern.
Figma — Q2 2026 Earnings Call
1. Management Discussion
Hello, everyone. Thank you for joining us, and welcome to the Figma Second Quarter 2026 Earnings Call. I will now hand the conference over to Kate DeLeo, Vice President of Investor Relations. Kate, please go ahead.
Good afternoon, and thank you for joining us on today's conference call to discuss Figma's results for the second quarter of 2026. On the call, we have Dylan Field, Figma's Co-Founder and Chief Executive Officer; and Prabir Mawani, our Chief Financial Officer. During the course of today's call, we may make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand, product development, growth prospects, business strategies and plans, partnerships, ability to attract and retain customers and ability to compete effectively. These forward-looking statements are based on management's current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements. Actual results may vary materially from today's statements. Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including our quarterly report on Form 10-Q for the quarter ended June 30, 2026. Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute or in isolation from GAAP measures. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call, which is posted to the Investor Relations page on our website. I would now like to turn the conference call over to Dylan.
Hi, everyone, and thanks for joining. I'm excited to share the results of another strong quarter for Figma. In Q2, we delivered $370 million in revenue, representing a year-over-year growth rate of 48% and our third consecutive quarter of accelerated growth. Q2 was also our first full quarter of AI monetization. And what we're seeing follows a pattern that is familiar to Figma, a core group of users driving outsized usage, paving the way for broader adoption across the organization. This gives us confidence in the AI consumption opportunity ahead. On the P&L front, net dollar retention rate was 136%. Non-GAAP gross profit dollars grew by 40% year-over-year, an acceleration on the previous quarter. Non-GAAP operating margin was 10%, reflecting the typical seasonal impact of Config. Free cash flow margin was 14%, and we ended Q2 with $1.7 billion in cash, cash equivalents and marketable securities. These numbers reflect incredible execution from the Figma team. They also show that as companies reimagine how they build products with AI, they are doubling down on Figma. This is because what Figma offers is unique, a performant professional-grade canvas where humans as well as agents can work side by side, deep product context that makes agents actually useful and full creative control through a combination of AI and direct manipulation. These differentiators are even more valuable in a world where code is a commodity and value is moving up the stack. We see a big opportunity for Figma as we make code a primitive on our platform and become the canvas for full stack creation. Let me explain. In June, at Config, we announced layes, which we plan to roll out in early access soon. AI has made individuals more productive than ever. Everyone is working with their own agent, exploring their own path in their own tool. Teams are moving faster, but they're often pointed in completely different directions. Collaboration takes a backseat as tunnel vision takes over. Individuals grow more attached to the direction they've explored and less open to ideas from their team. Code layers is designed to address these challenges with CodaLayer's interactive code lives directly on the Figleaves. Teams can edit designs and code or manipulate them visually.
They can also compare different variations of code-back pro types on the cannabis side by side. And this makes iteration fast in collaboration, the default. Codelayers is built on the same technical foundations as Figma make. Simply put, it's big to make on the canvas. And Figma make itself is getting more powerful. For example, in May, we started rolling out the ability for teams to start working directly in their production code base with make. Teams can go from idea to ship product without leaving sigma. One password uses Sigma from prototype all the way to code that ships to production.
The design systems team has built a full AI-assisted prorotobine pipeline with Figma make, complete with the custom MCP and the i-powered skills and not let some scaffold and publish new prototypes automatically. They've also opened Figma make access to licensed engineers. And when that process starts outside of Sigma, we've also made it easier to bring your work into Figma with our MCP server. At Clay, Designer Alex Fortney, was tasked with redesigning the company's tools panel, a surface undergoing its fourth redesign in the last 5 years.
Using MCP, Alex was able to expedite what would have been a tedious process by pulling all the existing components out of legacy code base and into Figma that way, she could audit the entire surface officially and altogether. As you put it, the Figma MCP has saved me countless hours of menu labor on all the Zisteme files and it's made it a lot easier for clays engineers to translate design in a production-ready code. MCP is what makes this possible at scale. Write-back support, let's teams push work into Figma, not just point and a right to Figma usage grew 75% quarter-over-quarter. Code layers pushing production with Tiga Make and credit consumption by expanding what you can do with code and Figma.
As AI makes code easier to write, everything though is starting to look at the same. These models are trained on what already exists. So what you get back is in distribution. It's the expected answer. The teams that will stand out are the ones with a bold point of view that are willing to put past obvious solutions. At Config, we launched motion and caters, 2 new expressive capabilities that used to require leaving Figma but now are native to our Canvas, and with igloos teams can build custom animations from scratch layer those on to existing designs or ask the agent to even generate a starting point. And this is all in the same cannabis that their team already works in.
Atlassian is a great example. The Design Systems team is building motion directly into the Atlassian Design system, giving anyone on the team the ability to design with and generate motion themselves is important because motion is something teams almost always want, but rarely get because it's time-consuming and it's expensive to build. As Senior Product Center Alexandra, Perera put it pigment motion turns animated illustrations from a specialist handoff into a system capability. Like motion, chatters make products feel live in new ways. With shaders, anyone can describe a texture or effect like liquid glass, and a sigma agent will build it for you. And then you can manipulate the output directly with fine grain controls that give you ways to customize your results.
Figma a similar approach to AI-generated media instead of tominersen the first prompt, you can scope generate outputs like Clay, connecting models and refinery results until what's on the canvas is exactly what you had in your head. Wevetools can now run inside Figma, which means teams can generate images and other visual assets without switching tools. This matters more as visual assets become a bigger part of how software gets made. In addition, this also opens up Sigma to new audiences we haven't served historically, in-house brain designers, creative agencies doing complex hands-on work.
Taxi Studio, a U.K.-based brand design agency Simple. We workflow to generate 3D renders for a design presentation with our client, Carlsberg, using 3 simple inputs, a beer glass a hop leaf and also a background. They create a starting point for brand imagery and then further find lighting, camera Ingal and texture. As designer Jack Go put it, all this took a day, whereas it would have taken a 3 specialist weeks and tens of thousands of pounds to ideate through these elements. It is such a great way to elevate and add richness to the work while staying very much in control. And it's this control that sets weave apart. The ability to express your creative vision exactly as you imagine it.
Together, motion, shaders and weave give teams the tools to make work that's genuinely distinctive, not just AI generated. The market is conserved is significant. And overall, it points to a larger shift. The line between building software and making creative work is dissolving. This opens up new mediums, new possibilities and new audiences for Sigma. The third opportunity is agents.
The Figma agent is built natively for design. It's fluent in Figma, increasingly powered by our own proprietary models because it works on the same cannabis as your team -- it has access to all the same tools that you do, including our new expressive capabilities like motion and craters. One way to think of the agent as is a capable design in turn, you can work off to everything from time-consuming tasks like documenting your design system to generate design visions that your team can build on. And because it works directly on the thing Figma Canvas, you can have multiple agents running in parallel, while you or a team focus on higher-level work. But the agent can do more than complete tasks, they can also build custom tools. And that's what generative pug ins are for. You can describe what you need and the agent will build something that your entire team can reuse, like custom charge generators or plug-ins that pull in live data directly onto the Canvas.
The response to generative plug-ins has been strong. As of July 31, and weekly plug-in creation was more than double what it was prior to the launch of generative plug-ins. Together, this represents a significant opportunity for our business. As the sigma agent takes on more work AI consumption increases and a ceiling on what a team can create in Figma moves up. The Figma agent rolled out an open beta in June and the early signs are promising.
As of July 31, over 50% of paid customers with more than $10,000 in ARR were already using the sigma agent on a weekly basis. The agent is also expanding who uses AI and Figma, not just how much as of July 31, more than 20% of weekly credit consuming users on paid plans were exclusively consuming credits using the Figma agent. The common thread across code new creative capabilities in the Figma agent is that they increase the surface for AI consumption and the possibilities for what and who can create Figma. Together, they can grow our total addressable market in ways that we are only beginning to capture.
More than 10 years ago, Figma introduced the Infinite Canvas as a shared space for teams to design software. The next evolution is a canvas for full stack creation, 1 place where anyone anywhere can reach for whatever tool they need to build whatever they dream up exactly the imagine it.
Before I close, I want to share some updates on our leadership team. First, our Chief Technology Officer, Chris Rasmuson, become Figma Chief Architect. After almost 10 years at Figma, Chris sees an opportunity to scale his impact by working directly on Tim's most business-critical engineering challenges, starting with Tom agent. We are kicking off the search for a new CTO. And in the meantime, the engineering team is responsible for our AI and editor efforts will report directly to me.
Additionally, our long-time security leader, Dev cave, will become Figma's Chief Security Officer. Deb and his team were early to adopt AI into Figma cybersecurity efforts, and I'm excited for Dev to step into this role. We also have 2 internal leadership transitions. First, after 7 incredible years, our Chief Product Officer, Yuki Yamashita, has decided to close his pigment chapter and take extended time off. UK has helped shape Figma's product and culture I'm sure ful for his dedication and impact. Lord Donikian who joined Figma as our Chief Officer in 2025, will expand her scope and lead Figma product function as well. Lord joined us almost a year ago after spending nearly a decade being design and product Meta for Messenger and Meta's AI efforts, design and product attitude and a strong point of view that she brings have already made a tremendous impact on Figma.
Lastly, Sheila Vashi, our Chief Marketing Officer, will be departing Figma at the end of August. Sheila has built strong marketing foundations for Figma as we have scaled our go-to-market efforts. Nyri Hordajian, Figma's longtime Chief Communications Officer, will be our new CMO Mary is a leader, I trust deeply. Her creativity and sharp perspective have shaped so much of our strategy in marketing and across Pega's business. I know her bold approach will further strengthen Figma marketing and differentiate our brand.
A year into our journey as a public company, the opportunity is bigger than even we expected. The tools are changing, the creative possibilities are expanding and Figma find itself at the forefront of the shift. We have so much work ahead and even more left to build for our customers. I'm super excited for it, and I know the team is, too.
And with that, I'll pass it off to Praveer.
Thanks, Dylan. As Dylan shared, our vision of becoming the canvas for full stack creation is resonating with customers. We consistently hear from our customers that they want to build more, move faster and push the boundaries of what is possible, all while elevating craft and taste. We're proud that our financial results indicate that we are delivering the right products and features to our customers as AI transforms the way products are built. Q2 was another record quarter.
Importantly, it was our first full quarter in which AI credit monetization contributed to results. Q2 revenue was $370 million, up 48% year-over-year and our third straight quarter of accelerated year-over-year revenue growth, just as importantly, that growth was accretive to gross profit in Q2. Non-GAAP gross profit for Q2 grew 40% year-over-year with our gross profit dollar growth, accelerating 9 percentage points quarter-over-quarter.
Let's start with AI credit monetization. As a reminder, we embed AI credits in each of our seats. Starting in mid-March, we implemented credit limits on all seats. Today, teams are able to purchase additional credits beyond these limits. A key signal we wanted to understand was how credit utilization would trend as customers began paying for incremental usage. A full quarter in, we are encouraged by what we've observed sustained usage is translating into revenue in 2 ways.
First, credits included in every seat make those seats more valuable, supporting upgrades, new team conversion and retention. As of the end of Q2, approximately 2/3 of paid customers with more than $10,000 in ARR added full seats compared to their prior renewal, which is consistent with prior quarters. At the same time, gross retention rate was stable in mid- to high 90s, highlighting the mission-critical nature of our platform for our customers.
Second, as customers exceed the credits built into their seats they can purchase additional credit add-on subscriptions on a pay as you go. We're encouraged by the paid conversion we're seeing and the continued broadening of adoption across our customer base. As of the end of Q2, over 80% of paid customers with more than $10,000 in ARR were consuming AI credits weekly. We are also continuing to learn how customers want to purchase scale and govern AI usage. We're moving quickly to iterate on our pricing model based on customer feedback.
Just this week, we began rolling out user level limits, giving admins more precise control over how AI credits are allocated across their organizations. We're also working to make it easier for users to request additional credits when they need them. There is meaningful room ahead as adoption deepens and we introduce new features and products that consume AI credits. Our products and features that are in beta and are still rolling out to customers, including Figma Agent, Figma Make on local code, motion, generative plug-ins and code layers do not currently consume paid credits. Early usage of these new products and features is trending ahead of expectations.
We're already seeing that the Figma Agent is drawing new users to consume AI credits as well as driving existing users to deepen their usage. As of July 31, over 50% of paid customers in more than 100 we're already using the Figma agent on a weekly basis. Now let's turn to our key metrics. In Q2, net dollar retention rate for paid customers with more than $10,000 in ARR remains strong at 136% even as we begin to anniversary our pricing and packaging changes from March 2025. We are continuing to both add new customers and go deeper with our existing customers.
In Q2, paid customers with more than $10,000 in ARR grew 34% year-over-year and paid customers with more than $100,000 in ARR, grew 46% year-over-year. We continue to invest in our go-to-market teams to support our global customer base. Last quarter, we expanded our footprint with a new office in Sao Paulo to better serve our customers in 1 of the fastest growing markets. We also now offer local data hosting in Brazil after introducing data localization in Australia and India earlier this year. All of these efforts have continued to help drive our global business and international revenue, which grew 50% year-over-year in Q2.
Now let me highlight a few of our customer wins from the quarter. One of the world's largest technology companies expanded its enterprise contract with Figma in Q2, and purchasing an AI credit add-on covering more than 25,000 total paid seats with the company now having more paid seats held by engineers than designers, a strong signal of developer adoption at scale. A technology infrastructure company expanded its AI credit add-ons multiple times within a single quarter, increasing its purchase credit commitment by 5x and from its first add-on as part of a company-wide push for AI native workflows across its product development more.
During a month-long trial of Figma Make, a global financial institution held an internal hackathon across its product, design and engineering teams, reducing prototype development time from a full quarter to a matter of days. New admin tools for managing user credits also unblocked a path to broader adoption by giving the company greater visibility and control over AI usage across teams.
Together, these productivity gains and stronger governance capabilities led the company to purchase a significant enterprise AI credit add-on subscription while AI credit consumption increased 2.5x quarter-over-quarter. Building on a successful 5-year partnership with 1 of Europe's largest software providers, we identified opportunities to further accelerate adoption of our AI products with targeted training for power users, we drove organization-wide adoption. The impact was immediate. AI credit consumption grew 2.5x month-over-month in the first month following the engagement and a new contract.
Turning to the income statement. Unless noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release, which is posted to our website. Gross profit grew and gross margin improved in Q2. Gross profit was $314 million, up 40% year-over-year and gross margin was 85%, up 2.5 percentage points quarter-over-quarter. The acceleration in gross profit growth and the improvement in gross margin this quarter is the result of our first full quarter of AI credit monetization.
Looking ahead, we have a clear set of tools to manage inference costs as adoption scales. We route across models based on task complexity, optimize across providers through our model agnostic architecture and are beginning to bring first-party models trained on Figma Design Corpus into specific design tests inside the Sigma Agent. For the right tasks, we believe those models can deliver comparable quality at lower cost and latency and will continue to represent a key area of investment and development in the second half of the year.
With the new product features rolling out in beta post Config, the goal remains to drive usage, retention and growth while improving quality, latency and cost ahead of GA. We do not charge our customers for their usage of products that are currently in IDA and we bear the cost of inference without offsetting consumption revenue. As a result, gross margin will vary from quarter-to-quarter in the near term.
Over the long term, we expect additional usage to drive revenue and gross profit dollar growth Q2 operating income was $36 million, a 10% operating margin. We hosted over 10,000 members of our community in San Francisco in Q2 for Config, our annual user conference. We view Config as an investment in our community and customers. This investment impacts our Q2 operating income and free cash flow. Inclusive of Config, our Q2 operating expenses grew at a slower rate than our top line. Q2 free cash flow was $53 million, a margin of 14%. The largest single driver for the year-over-year variance was cost related to our increased inference spend. The configure expenses also impacted our free cash flow. We ended the quarter with $1.7 billion in cash, cash equivalents and marketable securities, and we remain confident in the long-term cash-generating profile of the business.
Now let's close it out with our outlook. A reminder on our guidance philosophy. We provide a snapshot of our current view based on recent trends, including what we have high confidence in and where visibility is more limited, we observed sustained trends before fully incorporating them. For the third quarter, we expect revenue of $373 million to $375 million or 36% growth at the midpoint of the range. For the full year, we are raising our outlook to $1.463 billion to $1.467 billion, implying 39% growth at the midpoint, a raise of $40 million. The raise is reflective of strength in AI credit consumption for products being monetized today, positive early signal on the back of our new launches, strong conversion and continued expansion.
We are maintaining our full year non-GAAP operating income guidance of $125 million to $135 million, a 9% operating margin at the midpoint. This is the right moment to lean into investment given the strong signals we see. The question we ask ourselves is whether investment in product and go-to-market increases the likelihood that Figma builds durable advantage over the long term even at the temporary cost of near-term margin. Over the long term, we remain focused on innovating while driving durable revenue growth and maximizing operating profit dollars.
To close, Q2 was another strong quarter our first full quarter of AI credit monetization, a deepening of our product portfolio, a broadening of our AI workflows and an acceleration of growth in revenue and gross profit dollars and continued strength in retention and expansion. More importantly, we are confident in how this all will compound in the quarters ahead. AI is changing how team build software and how creative work is done, and that makes it more important.
we are pairing product velocity with a monetization model that will evolve alongside usage and that gives us confidence in durable, profitable growth from here. With that, I'll hand it over to the operator for Q&A.
[Operator Instructions] Your first question comes from the line of Alex Zukin with Wolf Research.
2. Question Answer
Two quick ones for me. Dylan, given the amount of products out there right now in the marketplace, from cloud design to sell to the Vicodin platforms. Maybe just level set and remind us what are you seeing on both top of funnel and upsell dynamics and cross-sell why Sigma seems to be winning even more in what looks like a more crowded field and the confidence that you have that, that differentiation should continue.
Absolutely. Thank you for the question. So I think that what we've seen overall is, as teams explore how to integrate AI into their workflows, they go through a journey on that. And what we've continued to see is teams doubling down on Figma as they come out of that process. Now to your question, as you mentioned, there's many tools they're solving different problems. Some of them are primarily coding tools. Others are more optimized for individuals or small teams. And I think it's really important to remind everyone that building software at scale is different. And the challenge is it just generating code or making sort of design assets that anyone in the organization might want to create or bathroom signs or green cards.
I think what's really important is to understand that our offering is really optimized for professional designers and unique. And the way we get there is a performance professional-grade canvas 1 where humans and agents can work side by side, deep product context that makes those agents actually useful and very importantly, full creative control through a combination of AI, but also direct manipulation and a ton of long tail functionality and workflow features, we've really built into a professional design environment that our customers still have plenty of requests for us to improve on.
And overall, you bring those capabilities together, and you layer the ecosystem that we built on top with MCP, with code layers coming and with the may continue to improve. And what we see when those all come together is that these tools are very good for different parts of the process and teams continue to come back and double down on Figma to build products.
I'll pass Perveer for anything was done.
No. The only thing I'd add, Alex, are some of the key indicators that I'm staring at, we're looking at the number of customers that are expanding at time of renewal within our 10-Ks customers. And you saw about 2/3 of those customers adding full seats at time of renewal. Our NDR rate of 136% remains healthy and strong. And it's built on the back of continued and steady expansion, strength in gross dollar retention and us now being able to overlay our AI credit model on top. So there's a lot of tailwinds that we get the benefit of, but it starts with product and it ends with product, and I think Dylan kind of did a fantastic job there describing it.
Your next question comes from the line of Gabriela Borges with Goldman Sachs.
I wanted to pick both of your brain key questions that we're getting with the stock being down in the aftermarket. Paver, the first question is on the sequential that you're guiding to for -- maybe just give us a little bit of color, it looks much more conservative than what you guided to in 2Q and then -- or much smaller in absolute dollars than what you guided to in 2Q? And then the flip side of this is on the gross margin. I know you have a number of cohorts, a number of new products layering in, all of which will be monetized when the time is right. So maybe just level set us on how to think about what the cadence of gross margin looks like in the medium term? And any kind of balance you can put around that for us?
Yes. Thanks, Gabriela. Really good to hear from you. So our guidance philosophy here remains consistent in that we provided a snapshot of our current view based on recent trends, including what we have a high degree of confidence in and we have and where visibility is a little bit more limited. We wait until we observe sustained trends there before fully incorporating them.
So both in Q1 and Q2, that's provided us more telemetry in how AI consumption will translate into revenue, which we've been able to flow through for the back half of the year. However, as we continue to create new surfaces that are going to draw even more credits over a longer period of time in agent, in code layers, in make and local code. Today, those products are sitting in beta or early access programs and are not drawing down paid credits. And so we've given ourselves an opportunity to do is to continue to invest to learn how those products actually mature to ensure that we're improving latency, reducing costs and improving quality before we transition those into generally available products.
And then as we make those transitions similar to the investment trajectory that we've taken, with our AI products thus far, we'll observe our ability to monetize them on the other side before fully incorporating them. And so this sort of philosophy actually also translates to our operating income. In that we have an opportunity here to both drive deeper investment into a number of these newer services, which is exactly what we've started to do and observe. And so that's why you're seeing deepening investment into the back half of this year is because we're really excited about the initial metrics and components there.
Your next question comes from the line of Michael Turrin with Wells Fargo.
I just want to ask a 2-parter on make, if I may. Dylan, I'm curious, given the rise in focus around open source and open weight models, if there's anything you see there that could potentially help further improve the overall position of make as you're talking to customers.
And for Praveer, we actually saw gross margin expansion this quarter. I think the 85% is a bit better what we're expecting. So just curious if you have an updated view on whether we're reaching a local bottom in any way, given you're now monetizing credit consumption or just how to think about the improvement in gross margin there.
I'll start with an answer around model and what we can see on the horizon, what we think might be possible. So I would orient everyone around 3 variables. One is latency. The second is quality. The third is cost. And as we work on first-party model development, which could include post trains of open source models, especially U.S.-based open source models. You will likely see us be able to further discrete certain tasks which could help with latency, it can help with quality and it can help with cost. And we think that's applicable not just to make it's also applicable to agent and to plenty of other surfaces across the Sigma platform.
And with that, I'll pass it Praveer for the second part.
Really good to hear from you again. So the thing that we're seeing over here is actually a consistent behavior that we've observed as we've had different product launches over time. The initial -- while we're seeing widespread use of our AI product. So about 80% of our 100-plus customers are using our drawing down credits on a weekly basis. What we are seeing is that we have an opportunity here to grow usage within those accounts, finding those initial champions and then expanding it over time.
In addition, as I was mentioning with the prior question, a number of the newer products that we just rolled out either in beta or early access programs are not drawing down paid credits today. And that then is an investment that we make in driving ubiquity of these newer services. So the trajectory that we've taken over the past year now where we have these periods of investment that then serves as a headwind to gross margin. And then in a period where we flip on monetization, we can then start to see the acceleration in gross profit dollar growth is 1 that I expect in subsequent periods.
So I think we're now, again, an investment period, an investment cycle as we continue to drive ubiquity of these newer products, and then my expectation over the medium to long term areas, then we'll then start to be able to translate that into gross profit dollars and more durable long-term growth as well.
Your next question comes from the line of Arjun Bhatia with William Blair.
Yes. Perfect. Thank you I wanted to ask maybe a little bit on the credit consumption of the products that are sort of drawing down these state credits. I imagine that's mostly make maybe agent here to come. But as we're looking at the back half guidance, should the sequential consumption of paid credits for those surfaces continue to increase. I'm curious what you -- I know it's just 1 quarter in, but I'm curious what you saw in 2Q and then as we're going through July, if that trends. If those trends accelerated or if there's any change there that you baked in guide?
Yes. Thanks for the question, Arjun. I think we've seen a number of different trajectories that customers take. Some were ready to make scale purchases. As soon as our credits came out of -- as soon as we began implementing those AI credit limits, [indiscernible] and really drove enablement with the champions there and saw credit consumption multiply over those same periods prior to them actually going and purchasing these scaled add-ons. What's really interesting here is our customers are looking to us for strategic thought and direction.
looking to us for strategic on direction. They're advocating for a partner. They want us to be a part of the conversation on how folks should be building product in the -- and as that starts to pick up, we fully believe that we should continue to have the opportunity to increase our credit consumption within the customer accounts as well. This is in addition to the newer services that just came out in beta in early access program, and you're exactly right that while they sit in data early access programs, they're not drawing down pay credit, but they will as they transition over into GAs over time, which then serves as a tailwind for us in the latter part of the year, early into this as well.
Your next question comes from the line of Billy Fiennes with Piper Sandler.
Bill, can you just context how in those MVP just trended year-to-date? You mentioned it's 75% year-to-year, but just help us think about how that tracked sequentially. Last quarter, there were some questions about the general competitive environment, but talking to time customers many or point in external eye workflows in the Sigma would be curious to the extent we can kind of on the magnitude of that occurring.
And if I can just ask 1 for Praveer. On the OpEx side, how is Sigma as high need kind of for year-to-date versus maybe your initial expectations going into the year.
First of all, just quickly, Chris, what you said there in terms of the 25% growth. It's actually quarter-over-quarter on the right Ts people that are using our MCP to get work into. And so we've been told to see the overall MTP growth as well as the specific growth on the right MCDaniel call. Now when you look at overall the picture at MCP, we see a bunch of a happening. We see people pulling work from Pika to go build it elsewhere. We see people pushing work into Pima. Overall, our point of view is that we really want to make sure that wherever you start, whether it's a cotingagent and you realize, wow, there's a lot opportunity to design better here or it's in sigmas you're starting with a very design for that bigness adding value to the process overall. And what we want as well is to offer people ways to complete that whole overflow in segment.
But overall, yes, we're bathe growth MTP. We'll be curious to watch the trade-off potentially between MDD and agent in the future. definitely, as you look complete more of the workload. But want to be if there's any change that creates in MCP and something that we're watching as well.
Your question on hiring. I think you continue to invest and build the team. But to your point, we are hiring fewer people today than we originally had planned that because we've been able to be the team that we have with AI and tools and see modernization of processes across the board I think we've been really thoughtful now as folks coming in and transitioning out to make sure that the process by which that someone is coming in and operating in is the right 1 for the way that people should be building companies in this new agent. So as our customers are going through this process of retooling as are we internally and I think we're really excited about some of the leverage that we've been able to find.
Your next question comes from the line of Rishi Jaluria with RBC.
Just 1 for me, I'll keep it to one. As you think about some of the success that you're having with some of the newer not just big oak, you've said a lot around that, but some of the exciting products that you saw on. Can you maybe walk us through not only rests driving usage of the existing customer base, but are you seeing situations where you're actually landing net new customer logos as a result of having these additional products and what that kind of expansion to look like.
Rishi, appreciate the question. I think largely, what we found is a lot of the new products here give us an opportunity to grow the number of folks that can sit on -- can sit and hold basis within existing pay plans, that's more within our larger customers as we go deeper and that will be evident and has been evidenced in our net dollar retention rate. I do think that there has been moments on the lower end part of the business and the overall number of customers that are on platform and we've disclosed this in prior quarters, we've seen acceleration in our ability to go and acquire customers over there as one.
So we've both been able to grow the overall number of folks sitting on paid plans while also then deepening with an existing on agent specifically, what we found is on kind of fill and dispose this in our prepared remarks, that we've actually increased the overall number of weekly active credit consuming users on paid plans. And today, folks that are actually drawing down paid credits or rather consuming credits on base plans via agent represents about 20% of the overall. So that in and of itself is broadening who can now hold the pace and luring the full over time as well.
Your next question comes from the line of Elizabeth Porter with Morgan Stanley.
I was hoping to get an update on the unit economics of AI credit revenue. I've just as you've gone through this full quarter of monetization. So where are some of the levers, whether it's the task-based model routing, the optimization of cross providers or repay models, they're already doing the lower in print costs, how we should think about those efficiencies affecting the incremental gross margin profile as you should scale.
Yes. We take a modest approach to the way that we're serving inference to our customers. And so that will continue to be a growing place of investment for us, especially as we deepen our investments on the first-party side. So today, we're able to serve an increasing share of requests that come in on agent via first-party models. And again, you don't have the content back and forth and trade-offs that we're making around what is -- are we able to serve that customer in that query with lower latency, lower cost and higher quality alongside of it. And so we'll continue to make a decision there and pull the right levers at the right moment in time. And as we demonstrated over the course of the quarter, we have the ability here to accelerate our gross profit dollar growth as we transition more and more of our credit consuming products as you being paid.
I'll just add, I think that there's so much we've done and so much more we can do when it comes to efficiency here. But again, you won't see us do that at the expense of quality or at the expense of lower latency, we think those are also ways to drive revenue when it comes to consumption.
Your next question comes from the line of Sami Chatterji with JPMorgan.
And maybe this is more for Praveer. Just the $40 million raise for the outlook for the year. I'm wondering how much of that is driven by the incremental credit usage that you're seeing rate to maybe other things coming in better, like higher seats, et cetera. And you now post the retail release of some of these AI products that you did at 1 say, are you now -- any change in thoughts in terms of how much the order you are you're going through that satisfy.
Yes. I'll be explicit here. I think right now at this moment, we are not taking credit for the products that are in early access programs or beta in our full year revenue outlook. I think that represents upside as we transition from these periods where the credits are not drawing down paid credits, and we condition those 2 DA products at. And then as a result, we'll be able to take more credit for it in our revenue outlook. Our philosophy here has always been to give you a transparent view of the things that we know and have a high degree of confidence over and in areas where we're still learning and or products, how to fully transition to being paid. We give ourselves an opportunity to learn and share that with you when we have a higher degree of company.
Your next question comes from the line of Nick Altman with BPIG.
I wanted to circle back on the proprietary model in Milan, you touched on it a little bit, but just with use cases and surfaces do you feel like the first-party model will take priority with your users? And then just given it sounds like the initial usage of your design agent is going really well. Like how much of that you attribute to your proprietary model? And do you anticipate the first-party model, maybe accelerating AI usage engagement in the near term as you expand that beyond the design in.
Yes, thank you for the question. I would say that first-party models oral will have use cases and ways they show up across our platform. Right now, a lot of it you can think about as how do you work better with design, how do you work better with Figma, and that is where we're seeing the most use cases show up. Over time, we think that will expand. At the same time, we're also still very much working with Frontier Labs, especially where customers wanted to like actually taking the design and building it and implementing that fully. That is something that I expect we will continue to work with Front Labs on in the immediate future, and we're grateful for those partnerships as well.
And in general, I think that the more that we can make is so that first-party models combined with frontier models end up at that the right place for mentioned between quality, latency and cost and where we can get the right place there, the more we'll see acceleration of usage in general.
Your next question comes from the line of Tyler Radke with Citibank.
Maybe just 1 for Veer. So we're looking some questions, obviously, really strong Q2 results. But as we look at the sequential guidance in Q3, can you just remind us some of the sets of assumptions you're making. It looks like sequentially kind of some of the smallest growth that you guided to. I know there's some moving pieces with price. But I guess more specifically, as you think about AI becoming a larger piece of the business, obviously, usage is more volatile than subscription fees. So how are you just incorporating that mix dynamic into your guidance velocity?
Yes. No, appreciate the question, Tyler. I think maybe I'll start on the product that R&R included. I won't release I think I've spoken about this a couple of times during the call. The products that are in early access programs or betas, they are not drawing down pay credit. We're going to wait until those transition over to GA products where we can observe how they actually monetize before taking credit for it in the guide. I think more broadly than that, in the back half of this year, we start to come up against the anniversarying of the pricing changes that we made last year. So there's a couple of tougher comps there. that we capture it into in Q3 and Q4. But largely, the key health indicators of the business and the places that I'm spending time and attention staring at, it's like what is our ability to go and drive consumption across our customers. 80% of our 100-plus customers are consuming credit on customers are consuming credits on a weekly basis.
What is our ability to go and add full see system of renewal within our 10-plus customers, 2/3 of our customers are added full pizza time of renewal, which is consistent what we've observed in prior quarters. We're both being able to go deeper within these customers go broader and then you then have the overlay of what a number of products that will roll out over time. And we do have some upside to the plan that should we execute we can achieve. But today, we want to give you guys a true view of what we know.
And then lastly, just to give you a flavoring of how our AI consumption revenue is actually translating or rather is being contracted. The majority of the structures today are a add-ons that are subscriptions with an individual and an individual subscription. So we have a fair amount of visibility on how those will translate over time. But you're exactly right that if more and more of that were to move to pay as you go or if we end up with more extended contracting structures, we could see more variability and when that gets recognized.
Your next question comes from the line of Parker Lane with Siebel.
This is Jack Machan on for Parker. -- over, you mentioned in your prepared remarks and in this last question, comers looking to -- or are you guys looking to iterate your pricing model based on customer feedback. I'm not sure you'll provide much on future pricing plans. But can you provide any color on what feedback around pricing has been from your customers? Are customers looking for more certainty around AI costs? Or are they becoming increasingly comfortable with paying consumption?
Yes. I think at a very basic level, and I see this even as a purchaser of a number of different AI tools is customers want control and choice. They want to understand that their investment here is driving return. And we need to be able to provide our customers with that same level sourcing control while also then being able to be really clear with the ROI that they're seeing on the other side of it. I think that from a true ROI perspective, we're actually seeing some really interesting early indicators. Folks that are relying on Cocone and then also using our MTP or seeing that the overall number of so consumed on the other side of it as they're translating into a coal be that much more efficient.
We're finding that folks like the ability to both lead with AI in certain places, but then have the full creative control on the cannabis. So not each action needs to be quite consuming as a result. There are things that we're rolling out on the actual pricing and packaging side, they give folks the ability to set user level controls, the ability to see restrictions in certain places. I think we want -- we hear from customers that they want to have the ability to draw down credit over longer periods of time. And as we think about the right ones and the right changes to make to our model, again, to provide customers with the control that they want and choice that they want.
My expectation is that will start to break down even more barriers and make the sales process that much more efficient over time.
I want to add before we end here that we are learning a lot. And so as the market federally as it comes to purchasing software on different ways that AI credits and consumption should be purchased. And so as we continue to learn, we'll continue to improve. And I think that will be something that continues to happen over the long term because I think we're still in the early days of what people want to see here and how the press that.
There are no further questions at this time. This concludes today's call. Thank you for attending. You may now disconnect.
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Figma — Q2 2026 Earnings Call
Figma — Q2 2026 Earnings Call
Starkes Q2: 48% Umsatzwachstum, erste volle Quartalsmonetarisierung von AI-Credits und Anhebung der Jahresprognose um $40 Mio.
📊 Quartal auf einen Blick
- Umsatz: $370 Mio. (+48% YoY)
- Bruttogewinn: $314 Mio. (+40% YoY)
- Bruttomarge: 85% (↑ 2.5pp QoQ)
- NDR: 136% (Net Dollar Retention Rate)
- Cash & FCF: $1,7 Mrd. Kasse; Free Cash Flow-Marge 14%
🎯 Was das Management sagt
- AI-Monetarisierung: Erste volle Quartalswirkung durch AI-Credits; 80%+ großer Kunden nutzen Credits wöchentlich.
- Produktstrategie: Fokus auf „Canvas für Full‑Stack Creation“ — Figma Agent, Figma Make, Code Layers und expressive Medien sollen Design→Code integrieren.
- Technische Priorität: Investition in eigene Modelle und Modell‑Routing zur Verbesserung von Kosten, Latenz und Qualität.
🔭 Ausblick & Guidance
- Q3: $373–375 Mio. Umsatz (≈36% Wachstum am Mittelpunkt).
- FY 2026: Erhöhung auf $1,463–1,467 Mrd. (≈39% Wachstum am Mittelpunkt, +$40 Mio.).
- Operativ: Non‑GAAP Operating Income unverändert $125–135 Mio. (~9% Marge); kurzfristig Margen‑Volatilität aufgrund von Beta‑Produkten und Inferenzkosten.
❓ Fragen der Analysten
- Unit Economics: Nachfrage zu Rentabilität der AI‑Credits; Management verweist auf Modell‑Routing, Multi‑Provider‑Optimierung und eigenen Modell‑Einsatz zur Kostensenkung.
- Guide‑Konservatismus: Management schließt Beta/EA‑Produkte (Agent, Make, Code Layers) von der Guidance aus, bis Monetarisierung stabil erkennbar ist.
- Wettbewerb & Adoption: Fragerunden zu Differenzierung; Management hebt professionelle Canvas‑Performance, Entwickler‑Adoption und starke Kennzahlen (Seat‑Adds, NDR) hervor.
⚡ Bottom Line
- Bewertung: Q2 liefert klare Wachstums- und Monetarisierungsbelege; Guidance‑Raise bestätigt frühe Kommerzialisierungserfolge.
- Risiko/Chance: Kurzfristig Volatilität in Margen durch Investments und Inferenzkosten; langfristig hoher Hebel, falls Beta‑Features planmäßig zu zahlungswirksamer Nutzung übergehen und eigene Modelle Kosten/Latenz drücken.
Figma — Q1 2026 Earnings Call
1. Management Discussion
Good day, everyone, and welcome to the Figma Q1 2026 Earnings Call. At this time, I would like to hand the call over to Mr. Brendan Mulligan.
Good afternoon, and thank you for joining us on today's conference call to discuss Figma's results for the first quarter of 2026. On the call, we have Dylan Field, Figma's Co-Founder and Chief Executive Officer; and Praveer Melwani, our Chief Financial Officer.
During the course of today's call, we will make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand for our products, including adoption of Figma Make and other AI features, our product development plans, business strategies and plans, and our ability to attract and retain customers and compete effectively.
These forward-looking statements are based on management's current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements. Actual results may vary materially from today's statements. Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including our quarterly report on Form 10-Q for the 3 months ended March 31, 2026.
Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute for or in isolation from GAAP measures. Our non-GAAP financial measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call, which is posted to our website.
I would now like to turn the conference call over to Dylan.
Hello, everyone, and thank you for joining. I'm looking forward to sharing the results of another incredible quarter at Figma. First though, let me tell you how I'm thinking about the opportunity ahead. Anyone building software today knows that we are living through an extraordinary time because with AI, what used to take months can now ship in sometimes an afternoon. Code is more plentiful, easier to write and the distance between an idea and its implementation is collapsing.
You've heard me say it many times in the past. When execution is cheap, design and creativity are the edge. And now it's not only me saying it, the entire world sees it too. The bottleneck has shifted away from can we build it and toward can we imagine something that's worth building. More design tools are launching, more people are creating, more software is now being built than ever before. And in this world where bits are abundant, what's scarce is human creativity, actual point of view, care and craft and judgment. This is what makes a product, a company, a campaign cut through the noise. Designers, builders and creatives, they all need tools that let them explore without limits and express their vision exactly as they imagined it. And that is what Figma has always been built for.
Our Q1 numbers reflect this momentum. Here are a few highlights. In Q1 2026, revenue grew 46% year-over-year to $333 million, accelerating from 40% last quarter and 38% in Q3. Growth came from across our business, seat expansion, retention, enterprise adoption, new users and of course, AI through Figma Weave, our broader AI capabilities and early traction from AI credit monetization, which started on March 18. Net dollar retention rate also increased to 139%, our highest rate in over 2 years. This is up 3 percentage points from last quarter. We also continued to generate strong cash flow. Non-GAAP operating margin was 16% in the quarter. Free cash flow was 27%, and we ended Q1 with $1.6 billion in cash, cash equivalents and marketable securities. Thank you to the Figma team for your focus and for your execution.
I'm also especially proud of how our team is adapting to new ways of working with AI during this time of exponential change. The momentum we've built gives us the confidence to raise our revenue and non-GAAP operating profit guidance for the year. Praveer will share more details on that in just a moment. But the story of our quarter, of course, goes far beyond the numbers. We're seeing our customers go bigger and deeper with Figma. So let me share a few examples.
First, Google. Google is a longtime Figma customer. Many of their most iconic products have been designed and built on our platform. As they build the next generation of AI native products, they're doubling down on Figma. The team designing agenetic Gemini experiences for millions of enterprise customers uses Figma end-to-end as their single source of truth from the earliest concept work all the way through to shipping. In their words, they can only "get to a level of detail that we want in Figma, that's not possible with vibe coding."
Lufthansa is another example of a customer going deeper with Figma to drive real innovation. Their Lido navigation product design team used Figma Make to prototype Lido mPilot, an integrated iOS charting app that streamlines flight navigation for commercial pilots. They did it with a level of fidelity that goes well beyond traditional prototypes, though. By connecting Figma make to their in-house API, the team could prototype dynamic, interactive map features. That way pilots could test real gestures before any production code was written. As they put it, pilots could really imagine what we were trying to show them. We validated our concepts before touching implementation. That's the goal of every product team, and we actually did it.
Teams aren't just going deeper at Figma. We're seeing broader adoption across the organization as well. Rocket Mortgage, for example, serves 1 in 6 American homeowners, unifying multiple brands and technology stacks into a single homeownership platform. To help scale that vision, the team built their design system directly into Figma Make as a shared template infrastructure for their entire org, accelerating adoption well beyond the design team. As design engineering lead, Will Hobick, describes it: "We're seeing adoption across the organization. Teams across Rocket are now using Figma Make to rapidly build dashboards, craft presentations and explore new customer experiences, all built on top of our shared design system and brand foundations." Design Director, Emily Strobl, had this to say on why it's resonating. "We've all experienced AI tools that just don't quite hit the mark or reflect our brand standards. Embedding our design system into Figma Make has fundamentally changed that."
In some cases, expansion goes even further beyond product development altogether. At NBBJ, one of the world's leaning architecture firms, Figma Weave, formerly known as Weavy, is changing how they win business. NBBJ's architects are subject matter experts in the industries that they design for. Their work is about understanding how a space needs to function, not just how it looks. So pitching a client used to mean commissioning photo realistic renders from an external studio. And that process took days and returned only 1 or 2 versions with little room for refinement. And now architects at NBBJ can just do it themselves. Figma Weave lets them translate their 3D models into precise, photorealistic renderings. They're able to generate and refine in real time, pushing until the result meets the exact bar that their work demands, dialing in time-of-day lighting, grounding a design in actual urban context, and getting the materiality just right. Figures placed at human scale make a ceiling height or entry sequence immediately legible to clients. The result is a faster pitch, a stronger presentation in full creative control from start to finish. Adoption of Weave at NBBJ is expected to triple in the next 3 months.
Across these customers and countless others, Figma remains the place where teams with the highest bar come to do their best work. Teams that know that creativity and craft are what we'll set them apart, they need tools that can match that ambition. Tools that let them explore freely and expressed their vision without limits. That's who Figma is built for. Our platform is where creativity lives and compounds, where teams can move quickly on their first idea and push further, questioning, refining, iterating with the best of AI, code and direct manipulation until the work is unmistakably theirs.
We see this in how our customers actually work. As of Q1, around 60% of our largest customers used Figma Make on a weekly basis. And over 80% of Make users on Full Seats continued using Figma Design for visual editing and broader exploration alongside Make. We love seeing how the ambition of our users and our community is always growing, and we are moving faster than ever to meet it. In the last few months, we shipped major updates to Figma Make that let users bring their own context into every prompt and give them more control over every decision as they build. We introduced new MCP capabilities that let agents read and write directly to Figma files so that teams can stay in control. In Q1, MCP weekly active users in Design grew 5x quarter-over-quarter. And we shipped updates to Figma Weave, including a timeline editor for refining AI-generated video.
Figma Make has driven the most AI usage so far, but MCP, Figma Weave and our AI assistant, which is currently in Alpha are meaningfully expanding the surface for AI consumption in Figma. All of this builds on what has made Figma the choice for the world's best teams building the world's best software. First, a performant enterprise-grade multiplayer canvas and platform, where humans and agents can work side by side with no silos, no handoffs, just the best ideas rising to the top. Second, deep product context that makes AI actually useful. The institutional taste, the historical decisions, the accumulated understanding of how your product should work and feel. And third, full creative control, the ability to prompt, code and manipulate visually all in one place, unlocking the full power of AI without giving up intent or the full range of what you can imagine.
Because in a world of abundant software, all of this together is what it takes to build products that stand out. And the companies that figure out how to harness human creativity alongside AI, those companies will define what the next era of software and creativity looks like. having spent over a decade building for the most creative community on the Internet, this is our moment. I cannot wait for you all to see what we're shipping over the next weeks and months, including at Config, our annual user conference in June.
With that, I'll pass it to Praveer.
Thanks, Dylan. Dylan shared some of the headlines and why we believe Figma is outperforming. I'll share a bit more detail on what we're seeing in our outlook for the rest of the year. AI continues to be an incredible tailwind for our business. Total revenue in the first quarter was $333 million, representing 46% year-over-year growth and exceeding the high end of our guidance. This marks our second consecutive quarter of acceleration in our year-over-year revenue growth. Our outperformance resulted from stronger-than-expected seat expansion across entire organizations driven by design's growing importance and adoption of our AI products, including Figma Make, MCP and Figma Weave. Our international business also contributed to our results with revenue growing 48% year-over-year. We also saw increased demand for our governance plus add-on and advisory services.
Our Q1 results are a testament to the team's relentless work building, shipping, iterating and listening to feedback from our customers. Retention and expansion metrics continued to strengthen in Q1. Our net dollar retention rate for paid customers spending more than $10,000 in ARR reached 139%, up 3 percentage points from the prior quarter and our highest level in over 2 years. Our outperformance in NDR was driven by strength in seat expansion and growth in our non-seat-based offerings, including AI add-ons.
We also saw acceleration in our customer cohorts. Paid customers spending more than $10,000 in ARR grew 37% year-over-year in Q1, a 5 percentage point acceleration relative to Q4 last year. Paid customers spending more than $100,000 in ARR, grew 48% year-over-year in Q1, a 2 percentage point acceleration relative to Q4 of last year. And our overall customer base grew to approximately 690,000 paid customers from approximately 450,000 in Q1 of last year, growing 54% year-over-year.
As AI gets better, Figma is accelerating and customer usage and workflows on our platform are deepening. Our platform and AI products drove faster growth for both new customer acquisition and expansion within existing accounts. Across all tiers, we're seeing customers grow seats and expand into new functions and teams. Within our larger enterprise customers, approximately 60% of customers with more than $100,000 in ARR were using Make weekly in Q1, up from over 50% just last quarter. In the long tail, we're also seeing continued acceleration in adoption of our AI features with new Pro team conversions which we view as a leading indicator for future growth up over 150% compared to Q1 of last year, demonstrating our ability to both expand TAM and convert existing users to paid plans.
A few of our notable customer wins from the last quarter include one of the world's largest hyperscalers running thousands of product and engineering teams across dozens of business units, unified its fragmented Figma usage across the enterprise into a single agreement with over 35,000 paid seats, one of the largest deals in Figma's history. A top global media and entertainment company that started with organic Make usage ended up with a full company-wide rollout. As teams adopted Make, every developer upgraded to a full seat. That growth happened organically, driven by how the product is actually being used, not by a top-down mandate.
We also saw some incredible wins in Q1 internationally. In India, one of the country's largest IT services firms signed our largest ever deal in the region, consolidating design and engineering teams on to Figma. And in Europe, one of the world's largest industrial automation companies with over half of its R&D workforce focused on digital development, more than doubled their dev seats on platform. Engineers at the company now outnumber designers on Figma, the team is now leaning into Figma's MCP to connect design directly into their development environment. The themes across our customers are clear. They're deepening their usage of our products, expanding their seats with Figma and finding even more value in their user experiences with AI products. In fact, in Q1, over 60% of paid customers with more than $10,000 in ARR added full seats compared to their prior renewal, consistent with what we observed last year and at equivalent expansion rates.
I want to take a minute to highlight the strong early signal we are seeing on AI credit monetization. We are at an exciting inflection point. On March 18, we began implementing AI credit limits for all of our seats and have been very encouraged by the usage trends we've seen since then. As of the end of April, over 75% of users on our Org and Enterprise plans who were previously over their credit limit continued to use credits and over 95% of those same users remain active on the platform.
Early enterprise customers who have committed are doing so at scale. For example, one of the world's largest enterprise technology companies in the middle of a company-wide push to become an AI-native organization after standardizing on Make, they are now purchasing additional credits to expand AI capabilities across product, engineering and PM teams spanning 7 business units. One of the world's largest professional services firms expanded their Figma investment after a company-wide Figma AI training drove a step change in adoption and embedded AI capabilities at the center of how they design, prototype and deliver client work across every major industry.
Additionally, as of the end of Q1, Pro teams that purchase AI credit add-ons had more seats per team and an average annualized spend of over 3x than that of teams that haven't purchased add-ons. Importantly, the surface area for credit consumption continues to expand. While today's credit usage is driven by products like Figma Make and our advanced image editing features, new capabilities currently in our early access program like our AI assistant, which enables new AI native creative workflows directly in the Figma Design canvas are expected to begin drawing on credits in the near future as well.
Our MCP enables developers and AI agents to build and interact with Figma directly within their workflows. We are seeing more teams convert to paid plans and upgrade seat types to access higher rate limits for our MCP. Among customers with more than $100,000 in ARR, those that were using our MCP grew full seats approximately 70% faster over the quarter than customers who are not using our MCP server. We expect this to evolve into a usage-based offering, but is currently available for free during the beta period. Q2 will be our first full quarter of credit monetization. We have been investing in more features to improve the customer experience including expanded admin controls, pay-as-you-go for Pro customers and more flexible contracting structures for enterprises. Our goal remains the same for our monetization model to support adoption rather than constrain it. Lots more to come here in the quarters ahead.
Now turning to some key income statement results. Unless otherwise noted, all metrics are non-GAAP. We've provided a reconciliation of GAAP to non-GAAP financials in our earnings release which is posted to our website. Gross profit in Q1 was $275 million, representing a gross margin of 82%. During the quarter, we saw a broader and deeper adoption of our AI features with our users benefiting from access to higher capability models, which in turn increased engagement and improved retention. With full seat AI credit limits now live, growing AI usage and adoption now translates into revenue, a key monetization milestone. We expect to continue to capture efficiency gains where available and have a clear set of levers to manage inference costs as adoption scales. This includes routing queries across models based on task complexity and leveraging our model-agnostic architecture to optimize across providers. We are also investing in first-party models trained on Figma's design corpus to improve performance on design specific tasks while reducing cost.
As we've reaccelerated our business, we've also delivered $52 million in operating income, representing an operating margin of 16%. Across the business, we've taken a first principles approach to rebuilding how we work across engineering, go-to-market and operations with AI tooling at the center. It's been energizing to see the creativity of our team in tangible wins and productivity across the board. We continue to evaluate our hiring needs to make sure we're operating efficiently. We believe the future calls for flatter organizational structures and more smaller, high agency teams that can move even faster, which gives us more capacity to invest and retool how we work.
Our Q1 free cash flow was $89 million, representing a free cash flow margin of 27%. We ended the quarter with $1.6 billion in cash, cash equivalents and marketable securities. As we previewed, we introduced an annual corporate bonus program in 2025, which was accrued for during 2025 and paid out for the first time in Q1 this year. This was a $56 million cash outflow and had a 17 percentage point impact on our Q1 free cash flow margin. Going forward, we expect to continue to accrue for the annual bonus each quarter and pay out in Q1 of each year. We remain confident in the long-term cash-generating profile of the business. We also remain committed to managing dilution responsibly. As our pre-IPO equity grants amortize, we expect that strong revenue growth, disciplined hiring and expanding operating leverage from AI will continue to drive improvement in stock-based compensation as a percentage of revenue.
Now turning to our outlook. A reminder on our guidance philosophy. We're providing a snapshot of our current view of the business based on recent trends. We include what we have a high degree of confidence in and where our visibility is more limited we look to observe sustained trends in the data before we fully incorporate the benefit in our guidance. For the second quarter of 2026, we expect revenue in the range of $348 million to $350 million implying 40% year-over-year growth at the midpoint. For the full year, we expect revenue in the range of $1.422 billion, to $1.428 billion, implying 35% growth at the midpoint and a raise of $55 million relative to our prior outlook.
Our raise for the full year is driven by 3 things: first, increased paid conversion across our customer base, fueled by the depth and breadth of AI across our platform; second, sustained broad-based seat expansion across every tier with teams and organizations opting for more dev and full seats to access our AI products and credits; and third, outperformance versus our expectations across credit utilization, retention and add-on purchases since implementing credit limits.
On operating income for the full year, we expect non-GAAP operating income in the range of $125 million to $135 million, representing a non-GAAP operating margin of 9% at the midpoint. This represents a raise of $25 million relative to our prior outlook. Our increase in operating income is driven by our revenue increase for the full year, operational efficiencies and continued optimizations we have made in our AI implementations. Additionally, while we are not issuing quarterly operating income guidance, we would note that Q2 operating income and free cash flow are historically impacted by Config, our annual user conference. We anticipate a similar effect in 2026.
In closing, Q1 was an exceptional quarter across multiple dimensions. Year-over-year revenue growth has now accelerated for 2 consecutive quarters. Net dollar retention rate reached its highest level in over 2 years, and the early signs from AI credit monetization give us tremendous confidence in the road ahead. As Dylan shared, design has never mattered more and Figma is built for this moment.
With that, I'll hand it over to the operator for Q&A.
[Operator Instructions] We will take the first question from Michael Turrin, Wells Fargo.
2. Question Answer
This is Richard Poland on for Michael Turrin. So first one for me is just with respect to the AI credit monetization. I know it's been only 2 weeks in the quarter and I think somewhere around 6 to 8 weeks since that officially went through. But how should we think about that starting to ramp and show up in the model into the Q2 and second half?
Yes. I appreciate the question here. So I think as where we stand, we're ahead of our expectations, and it's giving us confidence in the raise -- in our ability to raise our guide for the full year. We felt the momentum across big and small. Our paid customer base grew 54% year-over-year with the long tail of Pro teams there -- Pro team conversions rather, up over 150% in Q1 compared to the same quarter last year. In Q1, we're now up to approximately 60% of our customers over $100,000 in ARR using Make weekly and actually have seen over 75% of our org and enterprise users who were previously over the limit prior to credit enforcement continue to consume credits in April. And so as we sit here at the end of Q1, teams that are purchasing AI credit add-ons on Pro have an average ARR of over 3x more than teams that had not purchased add-ons.
And the part I'm candidly most excited about is all the amazing work that our team has still coming, which will increase the surface area for teams and organizations to experience the magic of our AI features. So when you think about the rest of the year for us, we very much believe that we've got a tailwind here from our credit monetization. And it's both going to be through the consumption that teams are actually seeing while also helping us drive continued seat upgrades on -- help us drive continued to seat upgrades for users and teams in the months ahead.
I'll also add that we're excited about the different surfaces that you'll see AI consumed on. For example, Weave is something that we're very excited about, and we really believe in the paradigm of node-base editing and the ways that you can create workflows where agents and models are working on the same canvas and you can move between the outputs of the various surfaces.
Your next question is Arjun Bhatia from William Blair.
Congrats on a great start to the year. Dylan, maybe I'm curious for you. It's been almost a year now or maybe we're a few months away since Make has been in GA. And I'm wondering what sort of change or evolution you've seen in the way customers and users are using Make. And it sounds like in your prepared remarks, you mentioned some enhancements that you had made around context and MCP. So I'd be curious how those new capabilities are resonating with customers and maybe enhancing the value of that solution.
Absolutely. And thank you for the question. And I think it's definitely the case that we'll continue to see, just like we've seen in the last year, paradigms evolve and expectations of our users evolve. Like we said in the prepared remarks, our users are incredibly ambitious. And we always intend to meet their ambition to make it so they can take full advantage of the Figma platform to create what's in their head. And when it comes to Make, we've been really impressed by the way that our users have stretched the platform to create everything from tools to prototypes to beautiful website designs to actual ship software. And some of them have just really done an incredible job of leveraging the platform to its fullest capabilities.
And at the same time, we believe there's so much more that we can bring to Make. And as we do the look back, some of the early technical decisions that we made did constrain us in ways that are obvious in hindsight, but we were not obvious then. We've corrected those. If you haven't tried Make recently, please try it again. It is already so much better. And in the weeks and months to come, I think you'll be amazed by the progress and so please check it out.
Up next is Keith Weiss from Morgan Stanley.
Congratulations on a really awesome start to the year, both in terms of what we're seeing in the customer base growth as well as your ability to monetize against that. Dylan, kind of digging into that sort of exponential change that you're talking about and the improvements that you're seeing in Make. I think the question a lot of us have is how these pricing models and the value proposition is going to evolve as we understand how customers are utilizing the tooling, whether it be Make or an MCP server or whatnot. Any initial kind of learnings that you could talk to us about in terms of how well the pricing model today is capturing that value proposition and how it might evolve going forward?
And then for Praveer, we saw some degradation in gross margins as AI picked up. You talked about monetization starting to kick in against some of that usage. Is there any kind of guardrails you could give us on where gross margins may be going forward? Like do you have any indication of what type of gross margin business is like AI activity is? And anything that could help us understand sort of the lower limits or whatnot of where those gross margins may come as AI becomes a bigger and bigger component of what you guys are serving your customers?
Thank you for the question. I would say that, first of all, I firmly believe, as I've talked with customers that the value prop and how it relates to pricing, what matters most is that we are providing the most value that we can to our customers, and we're solving their problems. And in this era, at least of where we're at with AI and pricing, that is what customers are looking for first and foremost. How it evolves going forward, I think we might see change where people become more discriminating on how much they're spending on tokens. And in fact, I think we're already seeing that with some of our customers. If the first chapter was, oh, gosh, we have to use AI and the second chapter was, okay, leader boards for token usage. Well, the third chapter seems to be, let's put some limits on this because this is real spend.
And some of the things we're doing around MCP, for example, and Code Connect actually do translate to more efficiency for our customers. And of course, we'll try to make sure that as we think about Make and other aspects of our platform that we're striking the right balance on efficiencies that our customers can use our product. I'll pass to Praveer to answer the rest of the question.
Yes. I appreciate the question, Keith. I think the spirit and sentiment that we get from customers is that they're looking to have more control. They want to have the ability to have governance on who gets access to what set of credits across teams, which we're really fast to address. And we've expanded admin controls. We've been exploring pay-as-you-go models for our Pro customers and more flexible contracting structures generally for enterprises. But to the broader question, I think we're seeing really encouraging signals and signs and early results on our AI monetization and we've got a number of early champions that are looking to continue to invest and work with us here.
And then to the spirit of your question on gross margin, I think in large part, it's hard to predict with precision where things will ultimately land. We've been completely focused around optimizing gross profit dollars. With full seat AI credit limits now live, any growing AI usage and adoption now translates into revenue, a much more natural offset to the growing use and customer value we're providing. In Q4, we previously demonstrated an ability to drive efficiency while also continuing to drive adoption and use. And our expectation is that we'll continue to have levers to pull in the future.
That includes things like routing queries across models based on task complexity, leveraging our model-agnostic architecture to optimize across providers and investing in first-party models trained on Figma's design corpus to improve performance on design-specific tasks while reducing cost. But the core focus for us right now, drive growth, ubiquity of our solutions, and we have every intention to ship and ship extremely quickly.
Gabriela Borges from Goldman Sachs has the next question.
Dylan, I really appreciated your case study in the prepared remarks on Google's usage. I'd love for you to talk a little bit about some of these new tools that are coming out from the LLM providers like Google Stitch and code design. I'm curious how you think about the impact those tools will have on the industry. And it sounds like there may be some underappreciated synergies between how Figma could potentially work with those tools as part of a bigger design cycle. So I would love to hear your thoughts broadly on that.
Absolutely, and thank you for the question. Well, I mean, first off, I just think that this is such an extraordinary time to build and as code becomes more commoditized and easier to write, design is clearly the layer above code and visual thinkers outnumber those who are comfortable in a terminal or an IDE. And so we expect this space to continue to heat up and to be the battleground for how software gets built. We also expect that tools around visual communication and creative design for purposes of marketing and advertising are going to be essential for breaking through the noise in a very crowded information environment online. And I think that's why we're going to see more and more tools come out. And to your point, many of them will be tools that we can integrate with and will actually be complementary and something that we can work with in our ecosystem. Others will be more direct competitors.
And so we, I think, try to understand that context by direct communication and conversation whenever possible and by having close relationships with our partners. And I think that overall, we have to focus on what we know best, which is for 14 years now almost, we've been deeply in the details of designers, designer workflows, and we have a team that is just absolutely incredible that cares so much about craft, about quality and about designing products with a strong point of view. And we're shipping faster than ever right now. So as I said in my remarks, I think that's what's going to take to win in this era along with that partnership and making sure that we're working with our ecosystem.
Your next question is from Alex Zukin from Wolfe Research.
I guess maybe first, this was your largest beat being public. And I appreciate that you guys had some really stellar new customer additions and a couple of really inspired key metrics. But maybe like what surprised you the most in the quarter that drove the outsized beat?
And then Praveer, maybe just, again, the quality of the beat is so high. I think it would be really helpful if you could help maybe set some guardrails around the low end of where -- how should we think about gross margins, particularly exiting the year? Like is this something that stays above 80% because of all the commentary and technical innovations that you guys are doing? Or do we pierce that 80% level at some point?
Yes. Maybe I'll take the spirit of the last part of your question there on gross margin. Like I was sharing with Keith, our focus right now is to drive gross profit dollars and really focus on growth. And so that is the key metric for us versus thinking that there's a specific floor that we want peers through. We want to make sure that we're driving ubiquity of our solutions. We're investing and investing deeply, and we feel like we have the best product and team behind -- team that's working behind it in order for us to win.
And then I think in the spirit of your first question, the beat and the core makeup of the quarter for us came from all different directions. Our product portfolio today looks extremely different than a year ago. And with each new surface and feature that we've introduced, we've made it that much more compelling to hold a paid seat. It's a consistent trend we've seen with users upgrading the full seats for access to higher rate limits on our MCP or access to products like Make. And so when you put that all together, all the components that helped us orchestrate a strength in our net dollar retention rate, TAM expansion, seat expansion, product expansion, tier expansion as well as pricing, we're all kind of kicking into high gear there. And you called it out there on Q1, we saw paid customer count growth overall, up 54% year-over-year, 10,000-plus customer cohort growth continued to signal strength and showcasing that they're continuing to add full seats across their teams at renewals.
Our international business is humming. We're deepening our investments in some of -- in stuff like our Governance+ add-on as well as advisory services. And it's early, but we are obviously seeing strong signal on AI monetization start to kick in. So as our pricing tailwinds from last year start to wane, we really get the benefit of some of these newer levers, and I'm excited about what the teams got cooking because I think it gives us confidence in the rest of the year here.
I'll just add on to the first part of the question around that floor. Well, plus one what Praveer said and also just stress that we always are working to be extremely rigorous about our short-term and long-term thinking. I think there are many aspects around delivering and playing for the big prizes when it comes to these new markets around AI where short-term thinking might create spend, but it's only -- you only engage in that if you believe in the long-term TAM and profile of the business that you're entering. And so we will continue to like apply that thinking and framework to the decisions we make and be very selective about the opportunities we go after.
The next question is Billy Fitzsimmons from Piper Sandler.
So Dylan, maybe for you. I want to expand on one of the earlier questions on kind of the evolving competitive landscape. I guess since last quarter, one of the cloud hyperscalers announced a seemingly similar product to make at the end of the first quarter. And then one of the frontier labs subsequently announced a design tool. And it feels like there's both coopetition with those vendors. But given kind of competition and how rapidly things are moving come up in investor conversations, first, Dylan, I know you just reported really strong growth, and there are a few application software companies in that ballpark. But just help investors think about Figma's differentiation in kind of this rapidly changing landscape. I know you've talked about that before.
And then second, anything from a numbers perspective in the second quarter, either from top of funnel, new logo usage standpoint, that investors should be aware of that suggests a change in competition. It really doesn't seem like it based on the strong guide for 40% growth, but anything worth calling out?
Yes. Thanks for the question. Obviously, this is a call about the first quarter, not the second quarter, so we'll stick to first quarter. And in terms of the competition or perceived competition, again, I think you have to look at each player individually. To speak directly, I'm very, very thankful for our partnership with Google. And we are big fans of the Gemini series of models. And we think that they're doing a lot of really interesting work, and there's a lot of opportunity to collaborate. And their labs product is not something that we're seen us gain the way of that nor do we see the effect as far as I can tell in a substantial way.
I think when it comes to Anthropic, obviously, we can't dismiss them. And I said that earlier, I'll say it again. They have the ability to train in first-party models and couple those with their own products if they choose to. And so we have to pay attention to that. And also, they're doing a lot of things, and we'll see what remains their focus. In terms of differentiators, I think there are many, a few that I'll mention today. Performant multiplayer canvas, I think, is something that people underestimate how hard it is to get those mechanics right and to really execute with quality on. This is something that has been a deep area of expertise for us for years. And I think there's a misconception that it only pertains to design. It pertains to many representations, including design, but also can pertain to code in the future.
Deep product context, I think, is another main differentiator that we have in terms of the context we can build from workflows, but also the context that our team has on serving our users. And finally, this ability to bring the best of AI and design and code and freeform direct manipulation together, all in one place, in one platform, that is what I think will ultimately create flow for people doing design work and serving their users. And I believe it will be our ultimate differentiator is the ability to go between these modalities rapidly.
Yes. And just to be explicitly clear there, we're confident in our guide for Q2. The numbers that we reported this quarter and the strength that we've shown in NDR and make usage for our largest customers growing from 50% as of the end of Q4 up to 60% as of the end of Q1. Pro team conversions up 150% year-over-year over the course of the quarter. The bottom line is customers are going bigger. They're going broader with Figma than ever before. You heard about Google, Lufthansa, Rocket Mortgage and countless others. And we're moving fast. And we have every history here of showing that we can meet the moment, and we're going to continue to out-execute there.
Next up from Stifel is Parker Lane.
If you look at the last few months since the enforcement of the credit limits here, I was wondering if you could talk about the split of those customers who have exceeded their limits buying more credits versus upgrading into full seats. And as you look out to '26 and these tools continue to improve, do you expect that split to be roughly similar? Or do you think there's going to be more of a likelihood that people choose one path or the other here?
I think customers are going to get both, right? It's a little bit too early to comment on the long-term mix, but we expect consumption to be an upside driver for the year. Our goal remains the same over here for our monetization model to support adoption rather than constrain it. And as we reinvest in the business, there's an opportunity for us to encourage use of our new products and features as we roll them out. And we get excited about the opportunity for our customers, for our users to experience all the magic of the products and features that we've got coming. So we've got an opportunity to both go deep with organizations as well as broad.
As we go deep, we'll drive more consumption, cross-platform use. purchases of add-ons like our Governance+ and advisory services. And then going broad, we'll license more of the team. And as they go broad in that way, they'll be able to unlock more features and use and potentially drive more consumption as well. And so we've got early signal right now, but we've been very excited by the usage trends we've been seeing since implementing credit limits on March 18 there. And I'd just remind you that as of the end of April, the majority of -- or rather 75% of the organ enterprise users who were previously over their credit limits, they continue to consume credits. They continue to consume credits over the month of April. And so when you think about it, the right model here is the one that meets the needs for our customers. And today, we believe that it's -- we're going to consistently see a mix of the 2 models, both seats as well as AI consumption.
And in terms of the product aspect of your question around when does a user choose inference versus when do they choose doing direct editing. This is something that I believe we really need to bring together and make -- it's a flexible approach where customers can choose the right thing at the right time, the right tool at the right time. And the more we can do that, the more customers can save on inference should they need to and also they can get the benefits of AI when that is applicable. There are some workflows in Figma Design that are 10 or 100x faster than AI. There are some workflows with AI that are way faster than if you're going to do it manually and really try to do like some bulk editing task. As we move to a world where Assistant expands in the alpha and ultimately comes out of alpha, more of our customers will be able to get those benefits in Figma as well.
Nick Altmann from BTIG has the next question.
Awesome. I kind of had a higher-level question, but this notion of code to canvas or canvas to code, it creates a bidirectional or maybe a round-trip workflow. And so Dylan, can you just talk about what you're hearing or what you're seeing from customers in regards to this workflow change? And then the follow-up is you've talked about how design being the differentiator gets accentuated in this new era. So if we look out over the next couple of years, like how much do you think your customers will adopt more of a code-to-canvas workflow approach? And does that potentially foster more users to adopt full seats rather than dev seats or collab seats?
Absolutely. Thank you for the question. I would say that First of all, just to frame up where I see us in the time line right now, we're in the early innings still of the product interfaces around models and inference. And so I don't think that anyone would tell you that an IDE or a terminal is where people are going to gravitate towards long term, if given the choice. It is instead, I think, the way that they can access these workflows today. And as that abstraction barrier goes up and they can instead access AI workflows, model capabilities through richer interfaces that are more accustomed to the task that they're trying to complete, I believe very strongly customer workflows will shift in that direction.
That said, it's where we're at today. And whether you're building an IDE, you're building in a terminal or you're building in Figma, we -- or you're doing both and going back and forth, it's really important to help our customers connect those dots and make sure that they're efficient with their token spend, but also the time that they spend translating between these surfaces. And that's why we do that. And we've been glad to see the usage of use Figma on the right side from models to and code to the canvas. And also on the MCP side, you heard it earlier, that's growing tremendously and people are getting real value out of that in terms of implementing designs and doing that in a much faster way, and there's still so much more we can do there. So we're excited about the round trip and has applications on our platform, too, even within the walls of Figma.
And everyone, at this time, there are no further questions. I'll hand back to our speakers for any additional or closing remarks.
Thank you all for joining. We are exceptionally proud of the quarter, and we look forward to speaking to you guys soon.
I'll also just finish off by thanking the team. Our team has been doing an incredible job executing with such strength and working extremely hard to meet the moment, and we have so much gratitude for everything they're doing, and I'm excited to see -- excited for all of you to see some of the stuff that we're working on in the weeks and months ahead. Tune to Config, our annual user conference in June and excited for you to see what we're shipping there and also to hear your feedback. Thank you.
Once again, everyone, that does conclude today's conference. We would like to thank you all for your participation. You may now disconnect.
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Figma — Q1 2026 Earnings Call
Figma — Q1 2026 Earnings Call
Figma liefert ein starkes Q1 mit 46% Umsatzwachstum, hebt Guidance an und sieht AI‑Credits als frühen Monetarisierungshebel.
📊 Quartal auf einen Blick
- Umsatz: $333 Mio. (+46% YoY), über dem hohen Guidance‑Ende
- Paid Kunden: ~690.000 (+54% YoY)
- NDR: 139% (Net Dollar Retention Rate), höchster Stand in >2 Jahren
- Betriebsmarge: Non‑GAAP 16%
- Cash/FCF: Free Cash Flow $89 Mio. (27% Marge); Kasse $1,6 Mrd.
🎯 Was das Management sagt
- AI‑Monetarisierung: Einführung von AI‑Credit‑Limits (ab 18. März) liefert frühe, bessere‑als‑erwartete Nutzungs‑ und Upgrade‑Signale.
- Produktfokus: Figma Make, MCP und Weave treiben tiefere Nutzung in großen Kunden (z. B. Google, große Hyperscaler, Rocket Mortgage) und fördern Seat‑Expansion.
- Betriebsmodell: Investitionen in Effizienz, flachere Teamstrukturen und erste‑party Modelle zur Leistungskosten‑Optimierung.
🔭 Ausblick & Guidance
- Q2: Umsatzprognose $348–350 Mio., ~40% YoY am Midpoint.
- Gesamtjahr: Umsatz $1,422–1,428 Mrd. (≈35% Wachstum am Midpoint), Anhebung um $55 Mio.; Non‑GAAP Betriebsgewinn $125–135 Mio. (≈9% Marge).
- Risiken: Q2‑Ergebnis/Cash beeinflusst durch Config‑Event; Inferenzkosten und Margen bleiben von der AI‑Nutzung abhängig, Management nennt Kostensenkungshebel.
❓ Fragen der Analysten
- AI‑Credits: Nachfrage und Fortsetzung der Nutzung sind stark (75%+ der zuvor überschreitenden Nutzer blieben aktiv); Management sieht Mix aus Credits und Seat‑Upgrades.
- Bruttomargen: Analysten forderten Guardrails; Management fokussiert auf Bruttoprofit‑Dollar und nannte Optimierungshebel (Modellauswahl, Routing, eigene Modelle).
- Wettbewerb: Fragen zu Hyperscalern/LLM; Antwort: Betonung der Differenzierung (performante Multiplayer‑Canvas, tiefer Produktkontext, Ökosystem‑Partnerschaften).
⚡ Bottom Line
- Fazit: Starke operative Performance und angehobene Guidance signalisieren, dass AI‑Features erste echte Monetarisierung liefern; Anleger sollten jedoch Einsatz und Kosten von AI‑Inference sowie Nachhaltigkeit der Kredit‑/Seat‑Mix‑Trends weiter beobachten.
Figma — Q4 2025 Earnings Call
1. Management Discussion
Well, good day, everyone, and welcome to the Figma Q4 2025 Earnings Call. Today's call is being recorded. [Operator Instructions]
I would now like to turn the conference over to Mr. Brendan Milligan. Please go ahead.
Good afternoon, and thank you for joining us on today's conference call to discuss Figma's results for the fourth quarter of and full year 2025. On the call, we have Dylan Field, Vigmu's Co-Founder and Chief Executive Officer; and Praveer Melwani, our Chief Financial Officer.
During the course of today's call, we may make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand, product development, growth prospects, business strategies and plans, partnerships, ability to attract and retain customers and ability to compete effectively. These forward-looking statements are based on management's current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements. Actual results may vary materially from today's statements.
Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including our annual report on Form 10-K for the year ended December 31, 2025. Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute for or in isolation from GAAP measures. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call, which is posted to our website.
I would now like to turn the conference call over to Dylan.
Hi, everyone, and thank you for joining today's call. 2025 was a massive year for Figma, and the fourth quarter was our best quarter yet. I'll share a few highlights. We delivered $304 million in revenue last quarter. This represents an accelerated year-over-year growth rate for the quarter of 40%. Our net dollar retention rate for customers with more than $10,000 in ARR also grew 5 percentage points quarter-over-quarter to 136%. And we generated cash with a non-GAAP operating margin of 14% and an adjusted free cash flow margin of 13%, ending the year with $1.7 billion of cash, cash equivalents and marketable securities. Our growth and momentum show that our strategy is working as AI gets better, Figma gets better, and we're shipping faster than ever. In 2025, we expanded from 4 to 8 products and launched over 200 features, including new AI native functionality. This momentum reflects amazing execution by our team. Thank you, Figmates.
We've carried that same pace and product velocity into 2026. In fact, we're accelerating. Just yesterday, we launched the ability to bring work from Claude Code directly into Figma. Let me show you how it works. Let's say, I'm a developer, building an app that looks like this. Many developers using AI start in Claude Code. The terminal is familiar, fast and powerful. So now I brought this app to a decent place. But if I want to make it truly stand out, it needs to be excellent. I need to think about the ways to make it awesome. And that's where things get interesting. Part of me wants to keep polishing, tweaking spacing, adjusting colors, refining every last detail. And you can see I've been painstakingly prompting AI, trying to nudge it towards perfection. But what I really need to do is step back and explore different possibilities. I need to see the big picture. To bring in the smartest people on my team and push toward bolder ideas. That's what design is about. Design is about giving people the freedom to explore. It's about asking what if. It's about seeing the bigger picture in pursuing the best possible solution. And it's hard to do that when you're exploring one idea at a time in a linear fashion with one screen, one prompt, alone in a terminal. So we're changing that. We're making design accessible even from Claude Code. And I can do that by simply typing send this app to Figma. And when I opened Figma, you can see the screen right there. These are fully editable design layers. I can adjust spacing, color, layout directly, which is much faster than all that prompting that I was doing earlier.
So now let's go back to the app. I can capture any part of it, and I can send it to Figma. Maybe I want to go to this specific state, so I can iterate on it more, or perhaps I just want this card because I'd like to explore how to make it better. In seconds, I can extract the key parts of the experience, and send them right over to the shared canvas and Figma design, where my team and I can explore freely. And you can already see my teammates jumping in. Greg is exploring a completely different look and feel. It's bold and unexpected. Anna is mapping the user journeys and identifying gaps in the experience. Now we're not just polishing one idea. We are exploring many together. I can build on their ideas using direct manipulation or even prompt AI for variations. What you're seeing is the power of design in this infinite canvas, the ability to bring everyone together on my team to explore and riff on divergent directions, to refine ideas with the precision and speed of direct manipulation. Now I can just use my hands to make edits, and I have the ability to zoom out and have the bird's eye view of what's going on and compare things side by side.
And once we've explored, we've aligned, we've landed on the best solution, we can simply go back to Claude Code and use our MCP server to bring these designs directly back into code. Claude Code de Figma is one example of how we're making it easier for teams to go from code to the Figma Canvas with a lot more to come. And of course, this builds on our existing Dev Mode MCP, which allows users to go from Canvas to code. We're excited about what we can do with additional partners via MCP to create a better round trip between design and production wherever you start. And for many of our users, that work starts in Figma Make, either as a rough idea, a detailed PRD or an existing Figma design. And in Q4, usage of Figma makes searched. Weekly active users of Figma Make grew over 70% quarter-over-quarter. And as of Q4, over 50% of paid customers spending more than $100,000 in ARR, we're building in Figma Make on a weekly basis. Figma Make has also unlocked new audiences and new use cases. In fact, of all Figma Make files created in 2025, nearly 60% were created by non-designers. We're talking developers, PMs, marketers and others inside the company broadly.
Let me share two stories from our customers that show how teams are adopting Figma Make. For the design and product teams at Cisco, deciding what to build and how to build it is a constant challenge. To move faster, they align by making, moving between Figma Design and Figma Make. Designers NPMs often work in the same make file, passing ideas back and forth. PM's lane fourth abroad strokes, designers refine them in real time. That speed is grounded in a strong design system foundation in Figma, where teams work from a shared set of standards. Make templates, kick off projects and can be adjusted to suit all types of purposes, increasing throughput across everything a team builds from interactive research readouts to early-stage product explorations and even custom internal tools. Building on that [indiscernible], a newly formed Agentic Design ops function uses make to explore AI-native workflows, often starting from static design files and turning them into interactive simulations. With Dev Mode now available through the Cisco App Store, many engineers who previously had view-only access have now adopted Dev Mode, improving speed and efficiency by working directly inside of Figma. Together, these workflows form a continuous system in Figma, bringing design craft, engineering and automation into one connected flow.
We found that for many teams using Figma Make, speed becomes a compounding advantage. At Flexport, teams use Figma Make to solve company problems faster. Every year, they bring the top 150 leaders of the company together. This year, they added a [indiscernible] with this challenge. Stop coming up with reasons to choose Flexport. Instead, you have 24 hours to solve one of the reasons why buyers don't choose Flexport. The competition run like a March Matis bracket had basically every team pitching their solution to one of these problems using Fingma Make, showing working apps within a day. One of the winners completely redid onboarding of factories to the platform, solving a long-time challenge. That idea is shipping to customers within the next few weeks. Another winning team used AI to process transcripts of customer conversations and then fed that data into Figma Make to automatically create custom diagrams. These diagrams made incredibly easy for sales to contrast before Flexport and after Flexport World for the customer supply chain. Figma Make is the preferred tool not only for the design team in Flexport, but also for even bigger transformation that is now underway, moving from a document culture to a rapid prototyping culture that solves problems faster. As the Flexport CEO told us the teams that do that with me are the teams that are doing really well.
We're especially excited to see how Figma Make is driving meaningful cross-platform adoption. In Q4, over 80% of Figma Makes weekly active users on full seats also use Figma Design. And to us, that means we need to go beyond features we've already launched. For example, the ability to copy UI generated Figma Make as layers into Figma Design or more recently, the ability to embed Make files as prototypes on the Figma Design Canvas. These are great, but we have an opportunity to drive toward more integrated capabilities that bring these services even closer together. But going from code to Canvas is only one part of the story. We're also focused on completing the loop and helping teams go from design to production as well. When this happens, we went work start in Figma, to flow easily into the tools developers use every day. With the Dev Mode MCP, which we launched last year, teams can pull design and code-based context built in Figma into the preferred Agentec coating tools. Customers like GitHub have told us that Dev Mode MCP is a game changer. KW's Figma to evolve and ship Primer their design system, where even small updates can affect more than 7,400 design tokens and tens of thousands of volumes of code. And at that scale, tight coordination between design and engineering is essential. GitHub uses Figma's MCB server and CoConnect to surface real production design system code directly in Figma. Each component is linked to its canonical implementation, keeping design and engineering aligned. Changes can be validated early before they cascade across thousands of tokens and components. Code Connect enables GitHub copilot agents to generate against authoritative components, improving accuracy and consistency from the start. But once required hours of back and forth during handoff can now move forward in just minutes.
Beyond using Figma internally, GitHub is also partnering with Figma at the platform level. And as a key partner in the GitHub MSP Registry, Figma makes its MCP server discoverable and ready to power AI-assisted workflows for developers using the GitHub product. While Velocity is critical. The best product teams are not defined by speed alone, you can go really fast and still get the wrong place. These teams are also defined by their craft. And in a world where software is growing exponentially, design, craft and point of view are what makes the best products stand apart, but delivering high craft creative work often means stitching together multiple tools, each optimized for a particular task. We're working to bring more of these advanced capabilities directly into Figma, so teams can spend less time wrangling all these different tools and more time designing incredible products and staying in flow state. One way we've done this is through our AI image editing capabilities, which we significantly enhanced with a new set of updates in December of 2025. In just a matter of weeks, these AI image editing capabilities were used more than 10 million times.
More recently, we launched new vector functionality in Figma Draw, vectorize uses AI to transform simple images like a hand-drawn sketch into dynamic vector illustrations that you can then tweak, refine and scale in Figma. As one user put it, this kind of work used to be painful and now it's a click. It's clear that our users create more ways to do their creative work in Figma, which brings me to our Q4 acquisition of Weeve, now for Maeve. Figma Weave's AI image, video animation and motion generation alongside precise creative control, expands the creative work possible in Sigma. Customers have told us they love how Figma Weave helps them enhance their creative process by bringing craft to everything from intricate compositions to showstopping stage visuals. One example of this is NVIDIA. For the NVIDIA CS Keynote, the team set out to create a high-fidelity group shot of 20 unique robots for the massive 12,000 keynote screen. For a moment of this incredible scale, they need a flexible workflow that allowed for rapid iteration without rebuilding the entire scene. The primary challenge was pixel density. Current generative models are limited to 4K or maybe 5k resolution mean that in a single pass, each robot would occupy too small an area to capture the fine detail. NVIDIA used Figma Weave to generate low fidelity 3D models that locked composition and camera angles. Then they created detailed 4k versions of each robot to fit the final frame, a custom AI agent also built in Figma Weave enhanced rapid lighting exploration before the full scene was generated, upscale to 12k and selectively refined for detail. The end results a cinematic keynote visual powered by a modular AI-driven workflow.
In the future, we believe far more people will create across the Figma platform beyond the confines of traditional product development. To meet that opportunity, we're pushing the boundaries of not only what you can create in Figma, but who can create in Figma as well. And we are accelerating into that future. AI offers a new creative starting point. It's like clay that you can shape. The first prompt does not need to be the final output. That's where humans come in. And whether this process starts in a terminal, a prompt box with UI and the thing with Canvas, a hand-on sketch, Figma is the place where it all comes together. Design is where all of that connects with code and canvas, speed and craft, agents and human judgment. We're excited about what this means for our users and for Figma. We're focused on building the platform that makes this future possible.
With that, I'll pass it to Praveer.
Thanks, Dylan. We're proud of how the team closed out the year with another strong quarter, punctuating a record 2025. Our total revenue in the fourth quarter was $304 million, growing 40% year-over-year and exceeding the high end of our guidance. For the full year, revenue was $1.056 billion, up 41% year-over-year, also above the high end of our guidance. Sequentially, Q4 was our best quarter of net new revenue added and drove an acceleration in year-over-year revenue growth. Our new product launches supported both new customer acquisition and expansion, driving improvements across all of our key business metrics in Q4 compared to Q3. Our retention and expansion metrics outperformed expectations in Q4. Our net dollar retention rate for paid customers spending more than $10,000 in ARR ended the quarter at 136%, an increase of 5 percentage points quarter-over-quarter and our highest rate over the last 10 quarters. Our gross retention rate for paid customers spending more than $10,000 in ARR remained consistent at 97%, reflecting the overall durability of our customer relationships. Q4 demonstrated momentum across each of our customer tiers. We ended the quarter adding 951 net customers spending more than $10,000 in ARR and 143 net customers spending more than $100,000 in ARR, growing that tier by 46% year-over-year, a 3 percentage point acceleration relative to Q3.
Breaking down growth across the quarter and full year, a few things stand out. First, we continue to see strong expansion dynamics as our customers broaden and deepen their use of our platform, driving larger renewals. We now have 67 paid customers spending more than $1 million in ARR, growing 68% year-over-year. Across tiers, customers are growing their seat counts expanding into new functions and teams and deepening their usage and engagement. Examples from last quarter include a hyperscaler, doubling their footprint with over 1/4 of new licenses going to product managers. A top 10 global bank embedding Figma even deeper in key engineering workflows, growing debseates by 69% and a Transatlantic Airline going all in with Figma on a multiyear commitment to elevate all parts of their operations from booking and check-in experiences, their loyalty platform and internal tools for crew and airport staff.
The pull from our customers is real. Second, we build deeper relationships at all levels within our customer base focused on positioning improving Figma's value as a system of record across design and product development. We are increasingly partnering not just with design champions but with central IT on driving the adoption of Figma's platform as a core part of their enterprise technology stacks, enabling more teams across the organization to collaborate in one platform, and we're seeing growing demand across our customer base for our Governance plus add-on as enterprises place greater emphasis on security, compliance and centralized governance. Third, we continue to invest in our international business. Our International revenue grew 45% year-over-year. While International users represented approximately 85% of monthly active users, they accounted for 54% of revenue in Q4, and we see meaningful runway for continued investment with the most recent being our launch in India last November. Finally, customers continue to renew into our new pricing and packaging through March of this year, which contributed a mid-single-digit benefit to full year 2025 revenue growth.
Turning to some key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release, which is posted to our website. Our gross profit for the quarter was $262 million, representing a gross margin of 86%. For the full year, gross profit was $931 million with a gross margin of 88%. While customer adoption of Make in our AI features continue to ramp with Make weekly active users up over 70% quarter-over-quarter, improvements and infrastructure optimization reduced our cost to serve each user and led to stable gross margins quarter-over-quarter. Our operating income for the quarter was $44 million, representing an operating margin of 14%. And for the full year, operating income was $130 million, exceeding the high end of our guidance with an operating margin of 12%.
On a year-over-year basis, our operating expenses increased as we invested in our people, infrastructure and systems to support the pace of our product development and strategic growth opportunities for our business. This was offset by the outperformance we recognized in our top line and gross margin, which flowed through to our operating income. Additionally, our full year non-GAAP tax rate ended at 14.5%, which we expect to remain consistent throughout 2026. Our Q4 adjusted free cash flow was $38 million with an adjusted free cash flow margin of 13%. We ended the year with $1.7 billion in cash, cash equivalents and marketable securities on hand. As we previewed last quarter, adjusted free cash flow declined sequentially in Q4, driven by continued investment in infrastructure and AI changes in the timing of vendor payments and a onetime $25 million IP transfer tax payment related to our acquisition of Weave. These impacts were partially offset by strength in customer collections.
We remain confident in the long-term cash-generating profile of the business. Before turning to our outlook, I want to briefly address stock-based compensation and dilution. Stock-based compensation was elevated in 2025 and reflecting the recognition of expenses attributable to the IPO, performance-based RSU vesting and the launch of our employee stock purchase program and equity issued in connection with acquisitions. These impacts were largely onetime and not reflective of our steady state compensation framework. Looking ahead, as revenue continues to scale, we expect stock-based compensation as a percentage of revenue to improve. We remain committed to managing dilution responsibly.
Now turning to our outlook for 2026. When we look ahead, we believe that Figma will continue to set the standard for how great products are designed and built. We're investing deeply in the business to define new AI native workflows and better support our customers as they adapt to new ways of working. At the same time, we've always been disciplined as we scale our business with a focus on the long term. For the first quarter in 2026, we expect revenue in the range of $315 million to $317 million, implying 38% growth at the midpoint. And for the full year, we anticipate that revenue will be between $1.366 billion to $1.374 billion, implying 30% growth at the midpoint. Our outlook reflects the sustained growth and momentum in the business that we experienced in 2025, including benefits from our new products and offerings, seed expansion from new and existing customers and international expansion. At this time last year, we had no customers consuming AI credits. Today, we're seeing approximately 75% of paid customers with over $10,000 in ARR consuming AI credits on a weekly basis, with adoption continuing to ramp. Our outlook reflects the seated adoption and usage patterns we're seeing today. We plan to refine our assumptions in the months ahead as we continue to both learn from customer consumption behavior and drive further AI adoption around new feature releases.
This March is when our model will shift to monetizing both seats and credits, a dynamic that is not reflected in our historical revenue results. We expect our full year non-GAAP operating income to be between $100 million and $110 million. This represents a non-GAAP operating margin of 8% at the midpoint. In 2026, we plan to accelerate our investment in AI and inference while building a world-class team and go-to-market motion. As a reminder, while we are not issuing quarterly operating income guidance, there is some seasonality in our operating income. Our Q2 operating income has historically been impacted by our annual user conference config, and we anticipate a similar impact in 2026. We also expect adjusted free cash flow to be relatively consistent with non-GAAP operating profit for the full year.
To close out, we are energized by the incredible year we had in 2025. We added a record number of new customers, exited the year with accelerating revenue growth while focused on product velocity, but we are even more excited about what's ahead for us. both for our customers and for the expanding capabilities on our platform.
With that, I'll hand it over to the operator for Q&A.
[Operator Instructions] The first question comes from Arjun Bhatia from William Blair.
2. Question Answer
Congrats on a very strong end of the year here. Dylan, if I could ask one just kind of philosophical question if we just step back a little bit. We've had I think a lot of noise made in the market about a genetic layer offerings like log to work and even open flaw. And I'm curious your perspective on what that means just for broadly? Like does it make it more of a differentiator? Do you think like user interface gets pushed to the back of this new Agentic layer emerges? Like what are sort of the puts and takes and the dynamics that you're thinking about as these new tools emerge?
Yes, absolutely. Thank you for the question for joining us today. So -- yes, I think right now, if you're willing to hand off mission-critical work to agents and just let them do it unsupervised, you're a very brave person. But that joke aside, I think it is the case that humans will continue to use software and increasingly agents will too. And I'm excited about that. I think that this creates more surface for designers to work with and design and think through. I will say that I think that the discourse around UI and how agents will change UI or not change UI, it is a bit extrapolating from current state. And humans are really hardwired to think and process information visually. Even as agents take on more work, people will still need to understand audit trust what's happening, and that requires visual interfaces that are human readable. Lastly, I would just say that we're going to see new interaction paradigms emerge here, and they'll have to be thoughtfully designed, adopted. For example, I think about Figma's multiplayer interface for Figma's Design or Canvas, and how humans work alongside other humans. And I think that we'll see agents also working alongside humans, both synchronously and accrete. And that, again, will lead to more intentionality around how to design software and what the surfaces are you need to design in the first place. In a world where coding is just no longer constrained, design, craft, point of view, that's the differentiator. And I'm really excited for that future.
Perfect. That's very helpful color. And then Praveer I had one for you. Obviously, it seems like the business is firing on all cylinders you had, growth acceleration in Q4, NRR ticked up. This is all happening before your credit consumption monetization kicked in. And so I'm just curious, like as you think about the 2026 guide, how are you benchmarking the range of outcomes from credit monetization post March?
Yes, I appreciate the question, Arjun, and good to hear from you. I think if I take a step back for a second and just think about what we've been doing as we've embedded AI across the entirety of our product suite. Everyone from a user who is a starter user on a free plan has access to credits that we've embedded within their seats. So for some time now, we've already started to see usage ramp. We shared in the prepared remarks about 75% of our 10k-plus customers today are actually consuming credits on a weekly basis. And this is an evolving number because we continue to introduce new AI features and services that continue to draw an ever-increasing number of credits over time. We based our guidance on an understanding of current observed seat adoption behavior and usage trends. We expect that to be refined as we both introduce new surfaces as well as really set to navigate at that point after we've begun to enforce our seat limits. There's an opportunity here to overperform as we build confidence in the observed usage behaviors, but we'll continue to add additional value to our users along the way. So we're excited here. I think we feel we've got some -- you've got a whole bunch of irons in the fire here, and we'll continue to refine our focus and story in the coming quarters.
Next question today comes from Michael Turrin from Wells Fargo.
I appreciate you making time, Dylan. I'd be remiss if I didn't start with another bigger picture question for you. The stats you're giving on Make seem to be hinting at new user types. Can you just speak to what you're seeing from customers using Make, and the user types that you're seeing? I think It'd be interesting to hear you just articulate on if this could be actually feed expanding for Figma in a world where investors are concerned around seat compression in most places?
Yes. Thank you for the question. And it's definitely something that we're excited about and tracking. As Praveer mentioned in his remarks earlier, we are seeing customers that are bringing, for example, product managers into the life cycle. And certainly, as we use Figma Make, not just internally, but also witnessed with some of our customers, internal tools, which can mean all sorts of different personas are quite interesting. So I think that overall, there's a lot of opportunity to start to reach into use cases like UX researchers and other use cases around the team as well. And with that said, I think that there's much more to do here, and we're excited to go do that.
And just as a follow-up, Praveer, I've gotten some questions on just the free cash flow comment you made in terms of the guide. Are you saying dollar amount similar to operating income? And if so, that's, I think, a bit lower than we were forecasting. So just any commentary on if that kind of make consumption based or just what the drivers and that comment were?
Yes. I mean I think there's a few things that will occur this year that are different from last year. And as we transition and as we continue to invest in the business, that was the spirit of the comments. So this will be a full year of us serving our AI features. We GA-ed them in the summer of last year. And as we start to see the continued ramp there, the expectation on what it does to margins is what we folded through to the guide. I think what is starting to get interesting here is as we start to introduce yet another monetization lever for us in the introduction of our AI credits. It starts to create a little bit more of a natural offset there over time. So I think we'll share more with you guys as we start to observe it. But right now, I think that's the best way to model it today.
Elizabeth Porter from Morgan Stanley has the next question.
This is Keith Weiss sitting in for Elizabeth Porter. And congratulations on a spectacular end to what was a great year for Figma in 2025. Two questions, one for Dylan, one for Praveer. For Dylan, you announced an exciting new integration with Claud and Entropic doing a lot of great innovation, but investors are somewhat worried about kind of letting the fox into the hand house, if you will, and trying to figure out where the dividing lines are of what is parts of the equation that are going to remain solely within kind of the Figma context, and what is Entropic going to be able to do. Do you guys -- how do you guys see that question? Like how do you see the dividing line between what is in the wheel well of Figma, and is always going to be in the wheel well of Figma versus what clot or what Entropic brings to the equation. And then for Praveer, on the price increases, getting a lot of questions from investors in terms of -- we understand mid-single-digit impact for the full year. Can you give us any sense of how that ramped in Q4? And what type of contribution in Q4? And how we should think about the price increase contribution to Q1, so we could better model kind of the slope for the coming year?
Yes. Thank you for the questions, and I'll start off with the first one. I would just say first that one thing that is interesting is how virtually every frontier lab is using Figma to design how they bring their malls to users and shape their product surfaces, and they are also been great partners with us. So that has been just interesting to see firsthand. I think zooming out our AI strategy is pretty simple. We always want to be in a place where as malls get better, Figma gets better. And easy to say, but you have to make sure that, that is the case for everything we do. And also that we can have an edge. And I think that one thing that answers your questions directly around sort of where are the lines between is, I would focus on tasks which are more verifiable versus non-verifiable. Design is inherently non-verifiable. And I think that's why you're going to see humans in the loop and even more focus on design as well because as code becomes something that more people can do with the assistance of models, the value will move up the stack. And with the value moving up the stack, I believe we're going to see an even greater focus on design. And we're already seeing it. I think with the higher [indiscernible] making and the ways that non-designers are getting involved in the design process. Praveer?
Yes. And I'll answer your question on pricing and packaging there. So just as a reminder, about 3 quarters out of the initial rollout of the changes that we implemented in March of last year, so the way that this is going to attract to revenue as folks are filtering in through the renewals, you have a growing benefit there over the course of the year. We lapsed that anniversary in March of this year, and then you'll start to start to see a winning benefit towards the back half of this year. So it's a little bit like a bell curve there where it grows over the first 4 quarters, and then it will wane over the next 4.
Gabriela Borges from Goldman Sachs has the next question.
I have follow-up on the conversation on Figma Make and ask specifically about some of the competition that you're seeing in the prototyping space. Give us a sense of what you're seeing in terms of perhaps consolidating budget within your customers, away from all the prototyping solutions. But I'm still seeing fragmentation in that world where customers maybe use multiple tools for prototyping and then put them into Figma when they're ready to go to the next phase of the design [indiscernible].
Yes. Thanks for the question. I think that some of the broad strokes we're seeing are really around the power of using Figma Make alongside Figma Design. And one stat that we shared in the earnings call is how over 80% of full seat users of Make are also using Design. And so I think that is an area that as we look ahead, we're really excited to win into more, is to really try to unite these surfaces better. We've seen it already with things like copy layers from Figma Make and the Figma Design or taking embeds from Figma Make and putting them in Figma Design. But it's just a start. And I think that there's so much more we can do here. And a big part of the platform differentiation we'll have will come from the unification of the services. I also think that it's really important to remember that the round tripping between code and design can really set us apart here. And I am just very bullish on the opportunity that could exist with that round trip.
Yes, that all makes sense. And a follow-up either for yourself, Dylan, or or Praveer. I'm curious the budget implications. When you see your customer go all in on Figma, what does that mean for how they're thinking about labor resourcing versus software resourcing. One of the things we've noticed as well, you put more powerful engineering type design tools into the hands of designers who may not know how to code. So how does the mix change between design-focused designers versus engineering-focused designers does that make sense? I'd just love to hear observations broadly on implications of Figma adoption for customer design and labor budget?
Yes. I'll start first. I think that some people are starting to call themselves design engineers. We've seen that in the past as well. There's been sort of surges around even 8, 9 years ago, people are getting really excited about calling themselves the engineers and then kind of it went back to product design and now that term is coming up again. But I would say, overall, we're not really seeing the roles blurring more the responsibilities blurring between roles, not just between design engineering and design, but the roles more broadly as you go out to the product design and life cycle, PM, engineering, design, research and marketing even responsibilities are starting to blur. People are feeling the need to be more generalist. So I think that it's hard to split in a very accurate way because so many people that are non-designers by title are starting to really engage with design tests, but I'll hand it to Praveer to speak more.
Yes. And then I think as it relates to the sales process and who we're having conversations with, I think we've over time, elevated the conversations to IT that gives us access to broader budget. And when you then kind of look at the types of users that we're bringing in, there was a few that we spoke about in the prepared remarks, the ones that stand up for rather -- the one that stands out to me is is the hyperscaler that doubled their footprint with about 1/4 of their new seats going to product managers. And this is not a unique instance. We're starting to see this happen more and more so throughout the customer base. And so our expectation is that we're pitching wider, we're preaching broader. And it's the overall platform that's ultimately winning here.
Next up is Rishi Jaluria from RBC.
Wonderful. Maybe two, if I may. First, for Dylan. Just kind of expanding on some of the dialogues that -- you have mentioned a lot of kind of next-gen companies in AI labs are working with you, and you've talked about some of the MCP integrations you have with [ Anthropic ] and others. How do we think about the opportunity for you to, over time, start building out more formal partnerships with them, having maybe even deeper integrations or kind of joint product development, maybe cascading a little far. Maybe just help us understand what is that potential partnership opportunity between you and some of these other AI natives look like in terms of enabling success in your customer base? And then I've got a quick follow-up for Praveer.
Sure. So I think that right now, as we think about our core with design, and just the opportunities that models provide as they advance with code, that is a big part of our focus. And the opportunity to partner deeply and to really make sure that we are thinking in the right ways about how models will continue to have new capabilities in the future. And then to make sure that we are accounting for that in our product road map as well as working closely and integrating well with various model providers is something that we paid a lot of attention to. I think going forward, as we think about some of the things we've seen with, for example, Figma apps on ChatGBT as well as Claud, there is definitely stuff that will explore there as well. But I think it is maybe secondary to the primary objective of just having that amazing ability to work and go from Code to Canvas and Canvas to Code and back again, that round trip is what we're really focused on and making sure that we are always meeting the criteria of as [indiscernible] better, we're gaining better.
All right. Very helpful. And then Praveer, in your prepared remarks, you closed out by talking about March is kind of when we're going to start seeing this more mix between subscription and consumption more of a hybrid. It's very consistent with what you've talked about before, and how the landscape seems to be shifting. Maybe as we think about that mix -- two pieces. Number one, how do you expect, given some of the early traction you're having with your AI native SKUs? How do you expect that mix to shape over time? And then alongside that, how do you -- what tools in your arsenal do you have to at least have visibility and predictability into future revenue. So the model install doesn't become overly volatile as we navigate through this change.
Yes. No, I appreciate the question, Rishi. I think the way that I'd frame it is we've already started studying this usage and utilization behavior. And we were prepping for this hybrid model for some time. We basically have telemetry into the overall seat rather the overall credit consumption on a per seat basis and what we've observed is it tends to be a power-law distribution where a subset of users within an organization are receiving outsized value and as such, are going over the projected limits that we intend to enforce. Now our expectation is that, that will continue to evolve as we introduce more services for folks to be able to drive down credits, will create more opportunities for us to have -- continue to shift that distribution further and further right. The way that our AI add-ons are structured, they're structured as additional consumption packs in addition to providing folks the opportunity to pay as you go. So in the instance that you're purchasing an add-on pack, it coterms with your subscription, and we have more predictability in that. And on the pay-as-you-go side, that is more meant to be for burst type activity. So ultimately, it will be a mix we're studying it very closely. And I think as we get post our -- the actual monetization date is when we'll be able to further refine our assumptions.
Your next question comes from Billy Fitzsimmons from Piper Sandler.
The FY '25 -- or the FY '26, I should say, revenue starting point was well above expectations. If I look at the operating income guidance, midpoint implies, I think, 7.7% non-GAAP operating margins compared to, I think, 12.3% in 2025. Just as we think about the drivers of this, what's kind of the breakdown between expected gross margin compression from AI investments in the product ramp versus maybe some incremental investments you plan on making on the OpEx line. And I know you don't guide to it, but any directional commentary on kind of gross margins in 2026 would be helpful.
Yes. I think your point on us continuing to invest on the AI side is what's showing up flowing through, both through gross margin and ultimately will hit our Op Inc and Op margin there. At this moment, we're not kind of sharing more specifics on the gross margin side, but it is meant to signal that we do see that there's a pretty large opportunity for us to take more AI features to a broader set of our users. And so that's what we've used in our guide to express our confidence and excitement to further invest here ultimately with the goal of driving growth and ubiquity of many of our solutions and durable growth over the long term.
If I can peak in one more.
I was going to add like if there's ever a time to put your foot on the gas to make sure that we are lean into the future. This is the time. So I just want to be clear about that. we can intend to invest here, do so responsibly but make sure that we are setting ourselves up to capture opportunity in front of us, which we think is very sizable.
Maybe on -- super helpful. Maybe just on OpEx, like a lot of companies this call it, earnings season or talking about expected AI-related efficiencies on the R&D line or the potential to increase product velocity there. How are you guys just thinking about that in terms of 2026?
Yes. I mean there's definitely opportunity there for us. I think what we're experimenting with is a whole bunch of different types of tools. We're iterating on different ideas and then observing overall efficiency of the team. We don't see that -- we don't see it as a tool that replaces our talent, but rather how can we augment the team that we already have. So we will continue to hire, but we will also be able to complement that with the efficiency gain by some of the tools out there as well.
The next question today comes from Parker Lane, Stifel.
This is Jack McSean on for Parker. Dylan, I'd love to hear you compare and contrast the benefits of your new quad code integration and Figma Make. Do you have any early indication on how customers are going to leverage all these tools that take you from 0 to 1 in the design process? And when will customers be using the quad code integration versus Make? Is it usually -- is it going to be a user preference thing, or will some projects be more relevant to one or the other?
Yes. I mean, I think it's -- there's plenty of times where I hypothesize, but it's probably not the format for hypothesis. And I would say that overall, this is very much in the too early team we just launched this yesterday. And so I am excited to learn more. But right now, we're still at a very early place here. I think, though, that if you look at the workflow overall, it used to be the case like even for sure, a year ago, perhaps even 6, 9 months ago, that a lot of people saw the workflow of product development is very linear. And you would do stuff like brainstorming and then design and then you'd code. And right now, we're seeing it in a place where people might start anywhere, and they won't be able to go everywhere. And so I think this plays directly to our strengths, making it so that you can really go into the Figma Canvas and with -- in the case of Make, really couple up Figma Make with Figma Design and make it so that you can go and explore divergently and really have that bird's eye view, zoom out and understand what's possible. The way I think about it is your sampling this infinite possibilities base. And you're trying to determine what are the right options to go explore in that space and then push them forward with design. And I think that you can do that through a code, you can do that through design, but code is more linear. It's more -- you're really advancing in one direction. And so you might be moving fast, but make sure you go into the right place before you go too far. Whereas design, you're really thinking about what are the range of possibilities I should explore, and you're weighting them and figuring out the trade-offs. And I also think that the opportunity for polish and craft and design is quite high. And that gets me very excited because we've really tried to make sure that direct manipulation works so well in Figma Design. And the opportunity to use your hands and just being [indiscernible] to flow, I think, is a big opportunity for our customers and it's so much more efficient than prompting a lot of examples. Overall, I would say Figma has the opportunity to be the place where all this comes together, the round trip, the direct papulation, the divergence of different possibilities as well as picking a solution and then saying, okay, I want to go to this up. Maybe that goes back into the Agentic development environment or IDE of your or choice or maybe in the future with long-running agents and increasing model capabilities, you can just do that from pigment design. So we'll see how the future evolves. Hard to predict when these capabilities come online, but we're really excited about our position here.
Yes. That was really insightful. And then just one more quick one for me. Obviously, the 4 products you launched last year, rightfully so, Make is getting the bulk of the attention but I'd be curious to get an update on draw buzz and sites. What's the usage been like, the feedback? And has there been any key -- any big surprises since they've gone to market.
Well, I would say for Make, obviously, getting tons of attention, you noticed that. And then as it comes to your draw buzz and sites, I would say that draw I mean, definitely, the engagement with some of the features we mentioned in the prepared remarks, has been really encouraging. And then I would -- around buzz and sites, I would say these products are still early in their life cycle. And so we are definitely working a lot here from our users as we always do. and we're seeing promising early traction. And while I don't have numbers to share, I think that there are definitely customer examples. For example, one is from a MAX7 customer, where with their creative team, they've been able to really be able to run a global holiday campaign through Figma Buzz and produced just an incredible amount of assets, I think, over 5,000 across 30 countries. And for the lot of scale you can get from buzz and also in some ways from Weave 2, which is a different use case, but has shared properties. We are really excited about how you can actually go create workflows for people. When it comes to sites, I would just say that there is a real need on the workflow side of going from a Design and Figma Design to something that is published on the web and that workflow need is incredibly important. And we're excited to help people go from designer production in general, but this is a very particular path. And whether it's Figma Sites or Figma Make, we're really watching closely how customers are completing that journey in Figma. And more broadly across all these products, we're watching the way that people use them making sure they have what they need and also pay attention to the constantly changing the environment and landscape that we're in, and that way we can plan and build accordingly.
Up next, we'll take a question from Alex Zukin, Wolfe Research.
I've got Dylan, maybe one for you and then one for Praveer. Building on some of the earlier questions that are at a high level. You have had the labs as customers or you have them as customers, they're deep partners, you're watching from the front row in terms of how the entire software supply chain is changing. What products or what usage maybe has surprised you, Dylan, to the upside? I mean, maybe specifically on Dev Mode and Make. And holistically, how are you thinking about tailwinds to growth from these products in fiscal '26 and a quick follow-up.
I'll actually punt that one to Praveer.
I mean there's a bunch of them that I'm excited about. I think we called out some of the momentum on make there. We grow our weekly active users, 70% quarter-over-quarter. And we start to see the adoption across our larger customers, the 100,000-plus customers going from 30% creating a make up to about 50% by the end of the year there. When I stare at Dev Mode, I think Dev Mode continues to be a very, very important part of the overall workflow. We see excitement not just from our -- from folks that are upgrading for the seat, but for folks that want to make use of Dev Mode MCP. It's an emerging trend that we found our -- is really resonating with our customer. We now have this opportunity really around trip given the integration partnership we launched with the Claudco to the Canvas yesterday. And our hope here is that what we're taking to our customers is a full product platform and suite. And as we do so, it gives us an infinite number of ways to position how these things kind of come together.
Got it. And then Praveer, maybe just for you specifically on Figma Make. What's in the guidance, is Make -- is it possible to think about Make or compare and contrast that contribution to growth relative to pricing in fiscal '25. Was it -- do you think it's going to be more or less? And are there any pricing tailwinds still contemplated in fiscal '26 in the guide?
Yes. Maybe I'll start with the back half of your question there. We're still going through the last set of renewals here. That are folks that are renewing under the new pricing and packaging that we launched in March of last year. So we'll anniversary that in March of this year, just -- which just so happens to coincide with the launch of our or make add-ons and credits. The way that we framed how make shows up and broadly, our AI features show up in our guide is we baked it based off current utilization and adoption trends, both on seat adoption trends, in addition to credit utilization patterns and trends. What we expect to see is as we've introduced more surfaces for folks to be able to draw down credits that we'll start to see more and more folks that would potentially land in the camp of needing an add-on. So what I would expect over time is that it's not necessarily going to be a fire out of the gate, but a slow build here with us wanting to make sure that we're really serving our users and meeting their needs. And then the onus is on us to continue to deliver value over the long term.
And everyone, unfortunately, that is all the time we have for questions today. This does conclude our conference. We would like to thank you all for joining. You may now disconnect.
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Figma — Q4 2025 Earnings Call
Figma — Q4 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz Q4: $304M (+40% YoY), über dem oberen Ende der Guidance.
- Umsatz FY: $1,056M (+41% YoY), ebenfalls über Guidance.
- NDR (Net Dollar Retention): 136% für Kunden >$10k ARR (annual recurring revenue), +5 Prozentpunkte QoQ.
- Bruttomarge: 86% in Q4 (Full‑Year 88%).
- Cash & FCF: Non‑GAAP Operating Margin 14%, Adjusted FCF‑Margin 13%, $1.7B Barmittel.
🎯 Was das Management sagt
- AI‑First Strategie: Fokus auf AI‑native Workflows und Integrationen (z. B. Claude Code, MCP) zur Rundreise zwischen Code und Canvas.
- Produktexpansion: Von 4→8 Produkte, 200+ Features; Figma Make als Treiber für neue Nutzergruppen (viele Nicht‑Designer).
- Enterprise‑Push: Stärkerer Vertrieb an IT/Governance, internationale Expansion (u.a. Indien) und Upsell in großen Kunden.
🔭 Ausblick & Guidance
- Q1 2026: Revenue $315–317M (≈38% Wachstum am Midpoint).
- FY 2026: Revenue $1,366–1,374M (≈30% Wachstum am Midpoint); Non‑GAAP Operating Income $100–110M (~8% Margin mid).
- Monetarisierung: Ab März Hybrid‑Modell Seats+Credits; ~75% der >$10k‑Kunden konsumieren wöchentlich Credits heute.
❓ Fragen der Analysten
- AI‑Monetarisierung: Analysten fragten nach Modellierung der Credit‑Erlöse; Management sagt Guidance basiert auf beobachteten Nutzungs‑ und Seat‑Trends, Verfeinerung folgt nach Live‑Monetarisierung.
- Make & Seat‑Mix: Nachfrage, ob Make Sitzwachstum kompensiert Sitzkompression; Management sieht Erweiterung der Nutzerbasis (PMs, Developer) als Wachstumspfad.
- Margenwirkung: Fragen zu Margenkompression durch AI‑Investitionen; Management bestätigt erwartete kurzfristige Belastung, langfristig Skaleneffekte erwartet.
⚡ Bottom Line
- Fazit: Starke Q4‑Execution und beschleunigtes Wachstum; AI‑Funktionen und Figma Make sind klare Wachstumstreiber. Anleger sollten Credit‑Monetarisierung und Margenentwicklung beobachten: Guidance signalisiert bewusstes Investieren in AI bei noch positivem operativen Ergebnis und FCF.
Figma — Q3 2025 Earnings Call
1. Management Discussion
Thank you for standing by. My name is Eric, and I will be your conference operator today. At this time, I would like to welcome everyone to the Figma Q3 2025 Earnings Call. [Operator Instructions]
I'd now like to turn the call over to Kate DeLeo, Vice President of Investor Relations and Business Operations. Please go ahead.
Good afternoon, and thank you for joining us on today's conference call to discuss Figma's results for the third quarter of 2025. On the call, we have Dylan Field, Figma's Co-Founder and Chief Executive Officer; and Praveer Melwani, our Chief Financial Officer.
During the course of today's call, we may make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand, product development, growth prospects, business strategies and plans, partnerships, ability to attract and retain customers and ability to compete effectively. These forward-looking statements are based on management's current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements. Actual results may vary materially from today's statements.
Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including our quarterly report on Form 10-Q for the quarter ended September 30, 2025.
Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute or in isolation from GAAP measures. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call, which is posted to our website.
I would now like to turn the conference call over to Dylan.
Thanks, Kate, and thanks, everyone, for joining Figma's Q3 earnings call today. After the Internet, AI is the most important technology shift of our lifetimes so far. I believe it's also an incredible tailwind for Figma and there are two reasons why. First, AI is uniquely good at code gen and asset creation, which means value is moving up the stack. And like we've said, for the last decade, design is a differentiator.
Second, as the frontier AI models get better, Figma gets better, and we built our strategy that way. Q3 was the best quarter in Figma's history. We crossed $1 billion in annual revenue run rate and delivered Q3 revenue of $274 million, a record for sequential net revenue added. This represents 38% year-over-year growth and is above the high end of the guidance that we shared.
Our team is working harder, moving faster and shipping extremely quickly. We're in the lucky position of [indiscernible], everything that we're building. This helps us launch products more quickly and with higher quality. Week-to-week, we're unlocking new capabilities that are resonating with new and existing customers.
In Q3, our net dollar retention increased 2 points to 131% driven by faster adoption of our new products and platform. We are investing to support our product innovation and growth across talent, AI and M&A. Even with these investments, we continue to generate profits with a non-GAAP operating margin of 12% and an adjusted free cash flow margin of 18% in the quarter. Ending Q3, our balance of cash, cash equivalents and marketable securities was $1.6 billion.
Brands and businesses are quickly realizing the design and craft are increasingly how they stand out and win. Our community is reporting that the design talent wars are fierce. And according to our own research, [indiscernible] on designers, 56% of those surveyed are engaged in design-centric tasks. And these same non-designers self-reported that they're spending more time and giving more attention to design-centric tasks than they did a year ago.
Today, design can start anywhere with any one, and it is no longer a linear process. PMs are visualizing their ideas as working prototypes, designers are mapping user journeys with chatbots, and developers are jumping into design details at the beginning of the process rather than just at the end. We are building our platform to meet these changing needs and is driving our momentum in a few key ways, product velocity, platform strategy, in the AI investment.
First, as I already said, we are building and shipping new features at an extremely fast pace. In Q3 alone, we launched more than 50 new features across every product on our platform. These launches are quickly giving our customers new capabilities and making new workflows possible, helping us bring Figma to new teams within the organization like brand design and marketing.
For example, [ Intercom, ] a leading customer service platform used Figma Buzz to develop hundreds of on-brand visual assets across social, e-mail and advertising for their annual AI Summit Pioneer. Using templates, designers were freed up to focus on high-impact work and marketers were able to customize hundreds of assets while maintaining creative integrity.
Our second momentum driver is our platform strategy, the ability to go from idea to product all in Figma, is unique. Our customers appreciate the interoperability of our products no matter where you start, you can move seamlessly across mediums. In today's workflows, this is not a nice to have, it's a requirement. For example, Flipkart, one of India's largest e-commerce platforms with over 500 million users renewed in Q3. And the company uses Figma for brainstorming, designing and moving to production. This connected workflow, help Flipkart launch Flipkart Minutes, its new Quick Commerce platform, 3x faster than previous launches. Flipkart is one of many amazing customers in India, and we're excited to officially open our India hub next week.
Rivian also uses the entire Figma platform, designed for one of the most complex digital ecosystems in the world, including multiple in-vehicle displays, web and mobile experiences and autonomous driving. Their unified design system in Figma maintains consistency across every single screen. By standardizing their production files and adopting [ CodeConnect, ] Rivian's designers and engineers now work in lockstep reducing [indiscernible] and accelerating ship times.
Lastly, we're building AI native workflows across our platform. I'm really excited about our progress here as Figma Make and MCP server are spreading Figma to new teams and new audiences. Combined with the platform strategy that I already mentioned, we're gaining momentum. During a period where some [indiscernible] tools are poorly seen slowing growth, Figma Make is being up. By the end of September, approximately 30% of customers spending $100,000 or more in ARR, were creating in Figma Make on a weekly basis, and that number has continued to grow. We will continue investing heavily in AI, and we will trade near-term margin to build the right long-term platform for our customers.
Today, I want to demo a few of these AI native workflows with Figma Make and Prompt to Edit, and I'll share some of the ways that our customers use them. Let's start with Figma Make, a product that lets anyone turn simple text prompts or existing Figma designs into a workable prototype or even a full web app with the power of AI.
We first launched Make in beta earlier this year and became available to all users in July. Since our last earnings call, the team has been working incredibly hard to improve Figma Make for our users. One feature we announced recently is the ability to bring your design system into Figma make. This helps to ensure you stay on brand and create outputs that are consistent with your design system.
So let's say, I'm on the product team at Duolingo, and I want to create a new lesson that allows me to review my previous mistakes. So I decided to use Figma Make to create that prototype for rapid fire, this or that exercise. And you can see it here. And press start, you can see how this is a working prototype, but like not amazing, definitely not on brand, something I could show people, but they might judge it by its looks rather than its merits. So how can I get to an equal footing with other prototypes?
Well, the design system is an incredible amount of context that has already been created in Figma, [indiscernible] doing goes, you can see their buttons, their labels, they keep going. And it's explicitly laid out and very clear how things should work. So now if I say export library to Figma Make, I can use that in order to make it so that I'm able to use that as a Make Kit. And with a bit of prompting, I can make it just perfect.
So you can see as I scroll down, I can even click these buttons, interact with the components. It's all here for me to use. This is an example of us taking that Make Kit and actually using it in Figma Make. You can see that when I click here, I've got Duolingo Make Kit being applied. And now when I click on it, you'll see the imagery and the overall brand and design language of Duolingo, pretty cool.
If I want to, I can also copy this design, and I can bring it into a design file, this is another feature that we recently launched. So one thing I might do here is take some of the objects. And let's say, I want to actually go and rotate this a bit. I'll put it behind this card in kind of a playful way. I'll take this one and do the same. And now I'm going to scale this all, and I'll make this a bit smaller, and I'll move this card back a bit. I'll clip content on this frame, and here I go.
So now I've got a design that you can kind of see what the things on the left and right might be, what [indiscernible] did as well as what's coming up. If I want to use Prompt to Edit, I can do that and show you the power of an upcoming feature that we have not launched yet, it's just in private alpha, but we're very excited about. So let's say that I want to go and say, okay, let's give this a fall theme and translate everything from French to Spanish. When I do that, the assistant will get to work. And it's going to, hopefully, give us some good results. Let's see.
All right. So it was able to infer from a fall theme that we should go orange and has changed it to Spanish successfully, and we can see that in the design. And if I wanted to go back, I can now go into my overall make prototype, and I can go prompt and actually copy and paste my design from Figma Design and to make in order to make it so I can update this entire view. You can see that the design has been copied in its context, communicated to make here as well.
So it's very exciting where we can head with us. You can also now use MCP to go pull that context from Make and Figma Design into code in order to go build a prototype or reflect your changes accurately in code as well.
All right. Now I want to share a couple of the ways customers are using these new products. Take Lowe's, a company that serves a range of consumers from DIY builders taking on a home remodel, to professionals doing large-scale renovations. Designing for these different customers used to be time-consuming and cumbersome. When Lowe's built [ Milo, ] their AI chat experience, Make allowed the team to rapidly explore the option space, designing and prototyping interfaces for different scenarios. For example, they prototype [ Milo ] to show a variety of tones, responses and flows. Because of the conversational experience, their design needs to adapt accordingly. And with Figma Make they can now test and refine design variations in just minutes. This helps Lowe's create world-class AI experiences with the accuracy and the flexibility they need.
Or consider Okta, a global leader in digital identity and security. They chose Figma Make as their AI prototyping tool because of its enterprise-grade security and trusted admin controls, and they quickly scaled it across teams. Okta's user research team has become a champion of the product. using Make to test ideas and build interactive prototypes for potential new features. During the recent Hackathon, one researcher use Make to prototype a new chat experience in just 5 minutes, and they're able to test it with customers immediately.
We're not only building AI native workflows directly on our platform. We also invest deeply in partnerships and product integrations. I want to highlight one in particular, Figma App and ChatGPT. People are generating a lot of information in chat sessions with LLMs. But what else can you do with that context? One way to use it, is to generate a diagram, a flow chart or a Gantt chart in FigJam. This integration lets you do that inside a ChatGPT and then lets you pop out to Figma platform to save, share or further edit. We see that this is useful for developers, creating system diagrams, researchers mapping out user journeys or even educators, building a flow chart for lesson plan. This integration is just one example. Over the past quarter alone, we've launched new integrations with Gemini, GitHub, [indiscernible] and many more.
Last week, we announced our acquisition of Weavy, which will join our team and platform as Figma Weave. AI has made it easy to create anything, but we believe the first prompt is just a creative starting point, not the final destination. Weavy combines lean AI models with professional editing tools on a single browser-based canvas. The result is an inspiring space for creative exploration. Let me show you.
[Presentation]
With this powerful yet approachable combination, Weavy gives creative new ways to channel their craft and their point of view. In less than a year, the Weavy team has built a passionate community from freelancers to Fortune 100 users. The testimonials that we heard from creatives using Weavy completely blew us away. We share the same community focus, maker spirit and deep love of craft. And together, we have so many ideas for what we can build. We're so excited to welcome them to Figma and plan to grow the team in Tel Aviv and beyond to support this work.
Between our product launches, the Weavy acquisition, our integrations and our AI investments, we accomplished a lot since our last earnings call, and we still have so much opportunity ahead.
Zooming out, with the explosive growth of software and creative assets, good enough is simply not good enough. It's merely mediocre you have to push beyond the prompt with design, with craft and with a bold point of view to build something that truly stands out. Design is the differentiator, how products, brands and businesses will win. It is part of why we brought on Chief Design Officer, Loredana Crisan, in Q3, who joined us after spending 9 years at Meta, most recently leading AI products. Just like our customers, we are also elevating design within Figma.
In closing, let me just say, we are so lucky to work with the most innovative companies in the world and with the most creative community on the Internet. Building for them motivates us every single day. And with that, I'll pass it to Praveer.
Thanks, Dylan. We're proud of our growth in Q3. Before we get too deep into the numbers, I want to reinforce our growth philosophy. We're focused on building a business for the long term and have been intentional about both where we invest and how we invest. Dylan discussed product innovation and differentiation of the platform across several product areas. That remains our focus, and this approach is working.
As we previewed last quarter, we deepened our investments in Q3 to build for the AI native workflows of the future. We will stay intentional with where we spend opportunistically improving efficiency in the short term but are absolutely focused on prioritizing long-term market leadership. With that, let's walk through our financial performance in Q3.
We ended Q3 with $274 million in revenue, representing 38% year-over-year growth. Our annualized revenue run rate is now over $1 billion. And on a quarterly basis, this represents our best sequential quarter of net revenue added on record. The general availability of Figma Make and our AI features in July has begun to accelerate a change in the business.
Driven by Figma Make adoption, we ended Q3 with 540,000 total paid customers, up from nearly 450,000 paid customers at the end of Q1, adding over 90,000 paid teams in just 2 quarters. We're proud of the traction and welcome these new users and teams to Figma and we'll be monitoring how these cohorts mature, continuing to improve our understanding over time.
As of the end of Q3, more than 70% of our customers were using three or more products. Teams expanded both their number of users and engagement on the platform. We saw a 27% quarter-over-quarter increase in customers signing multiyear deals, demonstrating that Figma is becoming the system of record for design and product development. After releasing our governance plus add-on last year and seeing strong adoption in highly regulated industries like finance and banking, we're now seeing broader interest among customers in many different sectors. The add-on is designed for organizations with advanced security and compliance needs like IP [indiscernible], enhance export controls and idle session timeouts.
Turning to our key metrics the combination of growth in new customers plus expansion within our existing customers, driven by our new functionality and products like Figma Make improved key metrics as compared to Q2. Our net dollar retention for paid customers with ARR of $10,000 or more ended the quarter at 131%, an increase of 2 percentage points quarter-over-quarter. We now have nearly 13,000 paid customers who spend more than $10,000 in ARR, adding over 1,000 paid customers in Q3. And we have over 1,250 paid customers spending more than $100,000 in ARR. We added 140 net customers in Q3, up from 88 in Q2, an acceleration in growth quarter-over-quarter.
Turning to our key income statement results. Unless otherwise noted, all metrics are non-GAAP. We have provided a reconciliation of GAAP to non-GAAP financials in our earnings release, which is posted to our website.
Our Q3 gross profit was $237 million, representing a gross margin of 86%. As we brought Figma Make and our other AI features to our entire customer base the cost to serve these products and features impacted gross margin. We believe that this is an investment in driving both the ubiquity of our products and is critical to the workflows of the future. Currently, we are not enforcing the credit limits on our full seats or charging for a consumption add-on. When we do, we anticipate it will offset some of the incremental inference spend.
Our Q3 operating income was $34 million with an operating margin of 12%. The outperformance we recognize in our top line flowed through directly to our operating income. On a year-over-year basis, our operating expenses increased as part of our broader philosophy around strategically investing for growth. We continued to build out the team, deepened our investment in Figma Make, both in the cost to serve the product and our go-to-market efforts and incurred incremental costs as part of our go-public efforts.
As part of the go-public process in Q3, we recognized a large onetime stock-based compensation expense as the liquidity condition on outstanding RSUs were satisfied. This expense resulted in a GAAP net loss in Q3. Going forward, we will continue to recognize stock-based compensation expenses and are focused on managing dilution. We anticipate that it will take several quarters for our stock-based compensation expense to normalize as our pre-IPO awards are expensed using the accelerated attribution method. Additionally, as a result of recent legislation, our non-GAAP tax rate decreased from 25% to 10%. In Q3, both our net income and EPS results benefited from this reduction.
Our Q3 adjusted free cash flow was $49 million with an adjusted free cash flow margin of 18%. The investments in Figma Make and our other AI efforts drove increases in spend on infrastructure and inference providers in the quarter. This plus the favorable timing of collections in Q2 brought down our margins quarter-over-quarter. As we continue to scale and increase spend on our infrastructure and inference providers, we expect some changes in the timing of our vendor payments based on business needs.
Looking ahead, we anticipate our Q4 adjusted free cash flow margin to decline sequentially given the continued AI investments as well as some onetime tax payments. Given the potential changes quarter-over-quarter, we will be managing our cash to an annual target.
Turning to our guidance for the fourth quarter and full fiscal year. First, our guidance philosophy overall remains unchanged. Our guidance is a snapshot of our current outlook for the business based on recent trends. Q3 was a record quarter on a number of fronts. Customers are adopting our new products, teams are growing their Figma usage, and we are becoming the system of record for design and product development.
Given the strength across our business, we are raising our outlook both on revenue and operating income for the year. We now expect revenue for the fourth quarter to be between $292 million and $294 million, implying 35% year-over-year growth at the midpoint. For the year, we anticipate that our revenue will be between $1.044 billion and $1.046 billion, an increase of $22 million compared to the midpoint of our prior range. This outlook implies 40% year-over-year growth for 2025 at the midpoint. While we intend to complement the existing seat-based licensing model with a consumption model, the outlook does not assume consumption revenue to be material this year. The strength that we're seeing in revenue will directly flow through to our operating income. We expect our full year operating income to be between $112 million and $117 million.
We are proud of the results we achieved and are executing from a position of strength with a disciplined investment framework and a clear long-term focus. With that, I'll pass it back to the operator to open it up for questions.
[Operator Instructions] Your first question comes from the line of Keith Weiss with Morgan Stanley.
2. Question Answer
Congratulations on another really impressive quarter and a really impressive new functionality, kind of walking us through, those demos, it really highlights the incredible stuff that Figma is putting together. And looks really cool as well.
Maybe a question on Weavy and the -- really 2 questions. One, where it kind of falls in terms of the design paradigm and how it expands your potential user base and how people are using the overall platform, one? And two, and perhaps a little bit more strategically, I feel like it implies something of where you think the value accrues in the AI tool chain, like between the design platform that Figma is bringing to the equation and the models themselves. And it almost kind of doubles down on the viewpoint that more of the value than I think many people appreciate is in the platform. Am I thinking about that correctly when you bring in Weavy and their ability to kind of stitch together the multiple models into 1 open canvas?
Yes. Thank you, Keith, for the question and the kind words. And I appreciate your excitement about Weavy. We couldn't be more excited. It's an amazing team and we are really excited to bring it on to the platform as Figma Weave.
When I think about why this team suns out, I mean, they've got with several other co-founders 20-plus years of experience in visual effects, animation creative production. And when we started to really dig in, their shared vision and the culture, I mean they felt like they're already Figmates. So we're really excited to bring them on board.
For those who are not familiar with Weavy yet, this is a product that allows you to compose AI model outputs with professional editing tools and really take a more modular approach. And the output from those models, I think of it as almost a new medium for creatives to mold sort of like clay.
To answer your questions, I think that in terms of the design paradigm where it falls into, for us, this is a product that -- we already have image fills. We bring in video to Figma Design but also across the platform. We already have like a way to go from prompt to image. But this is a way to make it so that those results and the content you're using are way higher craft, way more sculpted.
And if we think about it from the Figma Design side, a lot of people on the Weavy platform want to bring in layers and aspects of their designs into Weavy as well. And I think in that case, many of the percentage that we serve today, whether it be in product or brand, they will benefit from this.
Longer term, I think, yes, it will open up perhaps some new personas for us as well, but it's too early to say that right now.
The second question you had about the AI tool chain. I really think of it as this is the next step that's very important for us to make it so that people are able to bring higher craft to the results they have that they generate through AI models. And it really fits our thesis that we've held for a decade now where design is the differentiator. Craft is differentiator, your point of view is a differentiator, and that's how you're going to win this design craft point of view. And it's not enough just to go to that first prompt, you got to go all the way to the final destination, and I think Weavy and Figma Design will help you get there.
Your next question comes from the line of Rishi Jaluria with RBC.
Wonderful. It's great to see continued strength in the business. Maybe I just wanted to double click a little bit on Figma Make here. Really encouraged with the stats that you shared. Maybe 2 pieces on that I'd like to drill into. First, when we think about your $100,000-plus customers, that are using Figma Make today, what are the tangible results that you're able to see out of them, whether it's faster time to kind of design and deployment of applications, a greater velocity of innovation, maybe even a greater aperture of what addressable by Figma that wasn't there before.
And then over time, do we see this kind of just continue to go up into the right in terms of percentage where basically it just become such a core part of Figma that all your customers would -- are expected to use Figma Make in some shape or form? Or just how are you thinking about longer-term target in terms of Figma Make adoption and usage within your customer base?
Yes. I'll start off. Thank you for the question, Rishi. In terms of what the aspects of the platform are. I mean, first of all, the AI investments we're making like Figma Make are working, and it's incredible to see the progress the team has made here and we're only just speeding up further.
The quality of Figma Make and sort of the overall experience of it has gotten so much better even over the last month, and I'm really excited to make that quality continue to improve with these new features that we talked about in the prepared remarks like Make Kits design and copy it over from Make to Figma. So really excited for that.
We're also seeing a lot of high engagement with customers, new personas for some of those like product managers, user research and all sorts of other design adjacent personas and they can validate their ideas faster this way. It's also really differentiated, I think, as part of the broader Figma platform, interoperable with our other products. And I think ultimately, we need to get to the point where Make and Figma Design are really 2 sides of the same coin.
So yes, the results that people are driving. I mean I think it depends on which -- where they're coming from. We see, of course, long-tail behavior with Figma Make where more people outside of our traditional B2B structures, individuals, sometimes as well as small freelance teams or agencies. And then we also see more of a B2B use case. The B2B use case, I would say we are most focused on prototyping, making sure your idea works, but we're excited about how far we can go.
Whereas I think with that longer tail, people are going more straight to production and they're actually shipping. I'll turn it over to Praveer to follow up with more answers on other part of your question.
Yes. Rishi, good to hear from you. We're early in our rollout over here. We were making our AI products in July -- late July of this year. And the 30% of our $100,000-plus customers who are using Make on a weekly basis has only continued to grow since the end of Q3.
What we get excited about, is to where Dylan was going, as the product gets better as we continue to ship features, it continues to become a larger and larger part of the sales narrative and the pitch, the platform narrative continues to resonate with folks. Today, about 70% of our customers are using 3 or more products. And our expectation is as these products get better for us to continue to see improvement in those metrics.
Our $1,000 -- or rather our $10,000-plus customers, our $100,000-plus customers, their growth accelerated quarter-over-quarter in large part due to the new products that we launched. So we get excited about what's to come over here, and we really do believe that we're just at the beginning.
Your next question comes from the line of Arjun Bhatia with William Blair.
Perfect. And congrats on a strong quarter here. If I can touch on maybe Buzz and incorporated in Weavy together, like how do you see both of those kind of fitting together? Is there going to be a clear distinction of how you go to market with one versus the other? Or should those be kind of merging over time?
And I would love to hear maybe in this conversation, how you're also just targeting that new persona from a go-to-market perspective of the [indiscernible] over the sort of app design or dev user?
Absolutely. So -- what it gets us excited about both Buzz and Weavy, which are different tools with different expectations is to see the way that brand teams, creative teams are already using Figma, and then to make it so that the downstream consumers of their work are able to self-serve more. That's really exciting for Buzz. And there is an aspect of that in Weavy as well. But Weavy is much more about the production workflow and how do you actually craft a way to utilize various models in a modular way and make it so that you can take their outputs and transform them into an end result. And yes, you can also have a workflow process come out of that, which can be consumed.
But I think that Buzz is more of a surface that is particularly focused on the graphics case and keeping consistent. And I think that there's slightly different dynamics for both, I'll let Praveer follow-up.
Yes. And then in the immediate term over here, we will continue to operate as a stand-alone entity with the team joining as Figma employees and being able to leverage some of the resources that they get access to. We'll continue to sell the product on a stand-alone basis. And in the months ahead, we'll evaluate how we want to integrate the technology and their workflows. And it's good to hear, by the way, Arjun, that you're feeling better at this time.
The next question comes from the line of Kash Rangan with Goldman Sachs.
Very good results. Good to see the dollars added at a higher level than you had seen before and also good to see the net dollar retention move up very nicely. Dylan, we look at the success that Make seems to be having or is having, how do you think about the the halo effect that it's creating upstream in the portfolio? And how far are we or maybe it's already there, where it is trying to have a tangible ripple effect on the uptake of your core product design?
And also if you could touch upon the adoption rates and success, any metrics you could share for Dev Mode, that will be great.
And then one for you, Praveer, the effect of the price packaging on the percentage contribution to the revenue growth rate? Congratulations.
Thank you. I'll start with just a short comment on the ways that workflows are changing. I'll pass it over Praveer, I think most of the questions there were more for him.
One thing I think is really important in terms of your upstream question is to recognize that the traditionally linear workflow we've seen historically is really starting to change across some of our customer base, especially more of the early adopter types. And I'm very excited about this because what we're seeing is that people are going from perhaps it's making something in Figma Make, and they go and use that as a source of ideation, they might hop back to the idea stage, it might go to production. You might go into many different aspects of that workflow at various times, and it's really important for us to be able to help them traverse that. And I think that the power of our platform is that everything is there together.
And I think if you look at something like Copy Design from Make to Figma, you can start to see where we're going here and how Make and Figma Design could be really 2 sides of the same coin. And the inoperability story in that interop story will really improve over time, it's something that we're heavily investing in. I'll get Praveer to answer some of your questions about specifics of how this is happening.
Yes. No, I appreciate the question, Kash. I mean the way that -- the way I think about it and the way that it kind of shows up in our customer metrics is you look at both the $10,000, $100,000-plus customers, how those are growing over time, how we've seen the increase in our multiproduct adoption up to 70% of customers using 3 or more products as of the end of the quarter. All of that is honestly giving us confidence in being able to raise our outlook and guidance for Q4 and the rest of this year.
You raised a couple of questions there, both on Dev Mode as well as our pricing and packaging, so I'll tackle the Dev Mode one first. So we continue to see strong adoption and growth within our dev seats in particular. We're rapidly innovating there. We've added remote access to our MCP server. We made updates to Code Connect and introduce GitHub export, which allows you to export Makes into GitHub.
We're continuing to bring design and code closer together. We found -- we've accelerated our conversations with developer leaders and buyers over the last couple of quarters now post the launch of our MCP server. You take a couple of the customers that Dylan spoke about in the prepared remarks, Flipkart, National Australia Bank, both of which who were willing to make bigger swings in investments in the platform as they were growing their Dev Mode usage.
And then lastly, there on the pricing and packaging side. We're about halfway through the rollout, and we're largely tracking in line with our early projections. So no changes to the guidance that we rolled out last quarter. We anticipate that the benefit here is a mid- to high single-digit growth rate driver for the year.
With that said, we expect there also to be a benefit in 2026 as the pricing uplift is applied across the entirety of a first year of a customer's renewal on to the new model. And we do have a large number of those renewals in the back half of this year.
Your next question comes from the line of Alex Zukin with Wolfe Research.
Congrats on an awesome quarter. Maybe just a quick 2 for me. Dylan, the OpenAI integration and announcements at their Dev Day, maybe any thought on how that has any potential impact either top of funnel or potential cross-sell or revenue uplift implications for you guys over the next 12 to 18 months from those relationships?
And then Praveer, really nice to see the balance in net dollar retention back up. Any sense for how we should think about it maybe next quarter and over the next few as you guys have some of these multiple tailwinds kind of come to bear.
Yes. Thank you, Alex. I think it's definitely early days with the ChatGPT integration, and we're very excited about this. The ability to get Figma App out there on ChatGPT. But the use case, of course, is very much focused on FigJam right now and diagram. We're able to build this and ship it very quickly. And what you can do with it, you can generate diagrams, flow charts, scan charts, using your context from that chat session and then be able to iterate within ChatGPT a bit, through prompting and when you need to. For higher fidelity, you can go and pop out into the Figma platform to refine, to collaborate, save it to your account, et cetera.
And users are clearly excited about this. We've heard some really nice remarks. People have told us how much time it saves. And we're -- that said, we're still watching. We're learning how it's being used. So nothing to share yet on the monetization front. We're actively discussing with that with OpenAI. And overall, I think if you're popping out a bit of -- or zooming out, I believe that integrations in general, not just ChatGPT, but across the board are really important to our strategy. We added a lot of new integrations in Q3, and we're really excited about how we can connect with other products.
Yes. Thanks, Alex. I'll take the second part of your question there on NDR trajectory. We're proud of our NDR this quarter up to 131% for that $10,000-plus cohort, which increased 2 points quarter-over-quarter on an increasingly larger base. The drivers here are -- it's everything under this on. It's -- the platform approach is resonating. There is some benefit there to our pricing and packaging model. The newer products there that we've continued to roll out with more functionality are now reaching a wider share of audience within those particular customers now as well.
The one thing I'd remind you of is the tougher comp that we face versus our -- versus 2024, when we were rolling out Dev Mode for the first time. But we do feel good to be able to -- we feel confident enough to raise our outlook for the rest of the year due to some of the strength that we've seen both in the adoption of the platform, the adoption of some of our newer products and the performance of our pricing and packaging.
Your next question comes from the line of Brad Sills with Bank of America.
I wanted to ask about the strength you're seeing in new paid customers, really solid results there over the last couple of quarters. Any color on where you're seeing the incremental customer coming in here on the paid side. I think in the past, it's been pretty balanced across international and domestic. So I would love to get some color on that. And just where you're seeing traction in some of the newer customer additions?
Yes. No, I appreciate the question there. Candidly, it's a little bit across the board. If you look at the $100,000 plus customer -- or sorry, $10,000-plus customers, you look at the $100,000-plus customers, both of those accelerated quarter-over-quarter for us. If you look at our international revenue versus domestic, our international business is growing just slightly faster. I think over the course of Q3, we actually grew our international revenue about 42%.
So we continue to strategically invest in the international markets. We're investing across all of our new product surface areas. We've been able to bring in new folks onto the platform with Figma Make and many of our AI features. And so it really is a tide lifting all boats story over here, Brad.
That's great to hear. And I think you made some comments on how Sites is doing. I would love to get some color on how Buzz and Draw, these new offerings are seeing -- you're seeing traction there in the installed base.
So many of the things on Buzz and Draw are continuing to roll out to the customer base. And we're seeing the uptick on Draw as an example there within many of our existing customers as they look to elevate their craft and we get excited about some of the traction that we see over there.
Your next question comes from the line of Michael Turrin with Wells Fargo Securities.
I have two. I'll just ask upfront. Dylan, you mentioned in the prepared remarks that some of the [indiscernible] are slowing, Make is growing. I'd just be curious to tease out more observations around if that's a different type of customer, if that's sequencing or what, from your perspective is driving that?
And then Praveer, the 4Q guide looks stronger than we were expecting. It doesn't sound like Make or consumption is a meaningful contributing factor there. So just what's driving the Q4 strength and stabilization of growth? Is it some of the renewal dynamics coming through in Q4? Is there anything from Weavy for us to be mindful of or just any additional context there as well as useful?
Yes. Why don't I take that part of the question first, and then I'll hand it back over to Dylan to take the first part.
So what we've been actually seeing here is -- while we have rolled out -- we've rolled out our AI features to GA while we're on the consumption side, we have seen benefit in terms of new users that are expanding onto the platform on our full seats and an increase in the number of teams that are actually now sitting on paid accounts. So that actually -- that strength has been rolled forward into our guide into the rest of Q4 here as well.
On the Weavy side, both on the revenue and cost side, it's fairly immaterial or it is immaterial for our Q4 guide, but we'll continue to keep you updated there.
Yes, I can follow up on the first part of the question. For Figma Make, we are, I think, more focused than others on the B2B side where we believe that we'll see not only our platform have advantages but also lots of strength as we continue to build out from here our road map.
And the consumer side, of course, is still interesting, and we do see that behavior, too for that long tail. But what we are most focused on is how do we meet the needs of teams on the platform already and make sure that we are the best solution for them. Okta, I think, was a great example there where we were adopted by the product team and user researchers were able to validate their prototypes early visualize ideas and be able to put them in front of folks and get that buy-in, but also be part of the conversation.
And I see it as -- this is very aligned with our strategy of trying to expand the conversation around design of new participants, while also allowing a designer to be able to go deeper, level up their craft and raise the ceiling and very excited about where we're seeing both behaviors there on the BB side.
Our last question comes from the line of Mark Murphy with JPMorgan.
I'll add my congrats. So Dylan, we have heard more anecdotes that are showing that people that have tried to use prompt based design tools outside of the Figma ecosystem, what happens is they end up with a nice looking user interface, but then it falls apart when they try to take it into production, right, because they don't have the design primitives or the tablets or the brand assets. And so there's a lot of feedback that it becomes a heavy lift for engineering. And I'm just wondering if your customers are developing a clear understanding of some of the limitations of those competing products and maybe making a move to look a little more closely at Figma Make?
Yes. We're seeing not just increased adoption, but increased interest in Figma Make. And I think you recapped that really well. I think it's also important to just note that this has been part of our strategy for a while now to think about Code Connect, and the ways to tie Figma design systems to actual code because like you said, it's really important if you're writing code, if you're building a system, one of the first engineering principles that you learn, [ CS-101 ], is try, don't repeat yourself. If you already have something existing in the code base, you don't want to rebuild it. And you want to have that consistency and the more you have scale, the more that matters.
And that is a big part of what we're trying to drive towards is a better way to use your design systems, but also to use things like MCP to go to your code base and go build it. And so we're very much looking forward to figuring out how we can make that work with the entire platform and make that platform differentiate overall. Thank you.
Ladies and gentlemen, there are no further questions at this time. Thank you for -- this concludes today's call. Thank you for joining, and you may now disconnect.
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Figma — Q3 2025 Earnings Call
Figma — Q3 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $274 Mio (38% YoY)
- ARR: >$1,0 Mrd (Annualized Revenue Run Rate)
- Net Dollar Retention (NDR): 131% (+2 Prozentpunkte QoQ)
- Margen: Bruttomarge 86%, Non-GAAP-Betriebsmarge 12%, bereinigte Free-Cash-Flow-Marge 18%
- Liquidität: $1,6 Mrd Cash, Cash-Äquivalente und marktgängige Wertpapiere
🎯 Was das Management sagt
- AI-Tailwind: Management sieht KI als dauerhaften Nachfragetreiber; Figma Make treibt Adoption und Content-Generierung.
- Plattformfokus: 50+ Feature-Starts in Q3, 70% der Kunden nutzen ≥3 Produkte; Enterprise-Referenzen (Flipkart, Rivian) stärken System‑of‑Record-These.
- Investitionsdisziplin: Hochfahren in Talent, AI und M&A (Weavy), zugleich positive Non‑GAAP-Profitabilität – kurzfristig Margin‑Tradeoff für langfristiges Wachstum.
🔭 Ausblick & Guidance
- Q4-Prognose: Umsatz $292–294 Mio (ca. 35% YoY am Midpoint).
- Jahresprognose: Umsatz $1,044–1,046 Mrd; erwartetes Betriebsergebnis für 2025: $112–117 Mio.
- Risiken: Q4 bereinigte FCF‑Marge wird voraussichtlich sinken wegen KI‑Investitionen und einmaliger Steuerzahlungen; Consumption‑Umsatz dieses Jahr nicht materialisiert.
❓ Fragen der Analysten
- Weavy: Übernahme soll Weavy kurzfristig eigenständig lassen; langfristige Integration zur Erhöhung kreativer Marktfähigkeit angedacht.
- Make‑Monetarisierung: ~30% der Kunden mit >$100k ARR nutzen Make wöchentlich; Monetarisierung und Konsumptionsmodell noch in frühen Phasen.
- GTM & Pricing: Pricing‑Rollout zur Hälfte umgesetzt, erwartet mittelhohe einstellige Wachstumsbeiträge; Dev‑Mode‑Adoption und internationales Wachstum (Q3 Intl ≈42%) treiben Upsell.
⚡ Bottom Line
- Fazit: Starkes Wachstumsquartal mit erhöhter Guidance: Figma kombiniert Plattform‑ und KI‑Momentum, steigende NDR und Kundenzahlen. Anleger sollten erwarten: beschleunigtes Nutzerwachstum und strategische Investitionen in AI bei weiterhin positiven Non‑GAAP‑Margins; Schlüsselrisiken sind die Monetarisierung von Make/Consumption und kurzfristiger Margendruck durch KI‑Kosten.
Figma — Q2 2025 Earnings Call
1. Management Discussion
Thank you for standing by. My name is Kate, and I will be your conference operator today. At this time, I would like to welcome everyone to Figma Q2 2025 Earnings Call. [Operator Instructions]
I would now like to turn the call over to Kate DeLeo, VP of Investor Relations and Business Operations. Please go ahead.
Good afternoon, and thank you for joining us on today's conference call to discuss Figma's results for the second quarter of 2025. On the call, we have Dylan Field, Figma's Co-Founder and Chief Executive Officer; and Praveer Melwani, our Chief Financial Officer.
During the course of today's call, we may make forward-looking statements, including, but not limited to, statements regarding our guidance and future financial performance, market demand, product development, growth prospects, business strategies and plans, ability to attract and retain customers and ability to compete effectively. These forward-looking statements are based on management's current views and assumptions and should not be relied upon as of any subsequent date, and we disclaim any obligation to update any forward-looking statements. Actual results may vary materially from today's statements. Information concerning our risks, uncertainties and other factors that could cause results to differ from these forward-looking statements are included in our filings with the SEC, including the final prospectus filed in connection with our IPO and our quarterly report on Form 10-Q for the quarter ended June 30, 2025.
Our discussion today will include certain non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to, not as a substitute or in isolation from GAAP measures. Our non-GAAP measures exclude the effect of our GAAP results of stock-based compensation and certain other items. Reconciliations of non-GAAP financial measures to comparable GAAP measures can be found in our press release accompanying this call and which is posted to our website.
I'd like to now turn it over to Dylan.
Thanks, Kate, and hi, everybody. Thank you for tuning in today. I want to note that for today's earnings call, we're using one of our products, Figma Slides, which teams around the world use to co-create beautifully designed presentations. Figma Slides should look familiar to anyone who has used a presentation tool before.
One feature I want to call out is our grid view feature. This gives you a bird's eye view of the canvas and allows you to organize your presentation in a multiplayer environment. And of course, Figma Slides is interoperable with the rest of our platform. If I go back to our main slide view, I can edit or go into design mode. But for right now, I'm going to flip into presentation mode to get us going.
So Q2 was a strong quarter for Figma. We achieved $250 million of revenue, a new quarterly revenue record for Figma, representing 41% year-over-year growth. We also continued to operate profitably with a non-GAAP operating margin of 5% and adjusted free cash flow margin of 24%. With that said, I'm most proud of how our pace of innovation continues to accelerate.
Given this is our first earnings report, I want to set clear expectations that we may reevaluate our reporting framework in the future as our business evolves. For example, we might adjust our guidance philosophy or deprecate metrics we no longer believe are reflective of our business. And of course, if we do this, we'll share our rationale with investors. As you all know, we're at the very start of what I hope is a long-term relationship together. Our goal is to be clear and transparent. And with that, let's get into it.
Today, virtually every business is becoming a software business, and AI has made software easier than ever to create. In this world, we believe your design, your craft and your brand's point of view is what's going to make your product and your company stand out. Design is now the differentiator. It's how companies win or lose. And our goal at Figma is to build and expand our platform so we can do even more to unleash the taste and craft of our customers, who together are shaping and defining this next era of digital products. This goal is what guides our team, it guides our road map and it guides our investment philosophy. It's also what motivates me as I think about the years and the decades ahead of how we can expand our platform.
We're focused on building a durable long-term business that serves the evolving needs of designers and product development teams. Our focus drives our capital allocation decisions at Figma. For example, you should expect to see significant investments in our AI efforts because we believe AI will be critical to how software development workflows evolve moving forward. This means that we expect margins to come down in the near term as we invest in the long term.
And as I wrote in my S-1 founder letter, we do plan to take big swings if and when we see opportunities to invest, both organically and inorganically. We know this approach won't resonate with everyone, but we believe we have a massive opportunity in front of us, and we intend to capture it. Figma is where teams come together to turn ideas into the world's best digital products and experiences. What started as a design tool when we launched our closed beta back in 2015 has now grown into something much bigger, a single connected AI-powered platform that serves the entire product development process. We serve a deeply engaged global community of designers and product builders. They're passionate about their craft and they inspire us to think bigger every day, which brings me to Q2.
This May, we brought nearly 10,000 members of our global community together in San Francisco for our annual Config conference. Hundreds of thousands of users also tuned in to watch virtually. And then the next week, we hosted thousands more in person at Config London.
At Config, we launched 4 new products, doubling our product offering. These products are Figma Make, Figma Draw, Figma Sites and Figma Buzz. We also launched our Dev Mode MCP server, which speeds up developer workflows by bringing context from Figma Design into any surface that consumes MCP. For example, IDEs like VS Code and Cursor.
In Q2, we also made 2 exciting acquisitions, a company called Modyfi to support our work around visual expression and Payload, an open source company with a strong developer community that offers a leading headless content management system and application framework.
Now I'll go into more detail on each of the 4 products that we launched at Config. First up, Figma Make. Figma Make is our new prompt-to-code product that allows you to use an existing Figma design or natural language to create a fully functional prototype. You can also build working apps and publish them directly to the web. Teams tell us that the speed of going from an idea to a working app is a game-changer. Figma Make gives anyone the power to visualize an idea in high fidelity and validate a concept with something realistic. And in some cases, their creation can even be the real final product. This is important because so much of what has made product building a challenge is slow cycle times and not having to wait to explore the full option space of your ideas. Now you can do this more quickly and sometimes really quickly, in a matter of minutes with Figma Make.
So let me show you how it works. This is Figma Make. On the bottom left, you'll notice a chat box where you can type in a prompt to generate a full dynamic web app. Now you may have seen other AI vibe coding tools like this and perhaps you're wondering what makes Figma Make different. Figma Make's superpower is the design context it can tap into to create higher quality outputs even if you're not a designer yourself.
Let's say I'm a product manager on a team building a fitness app. I have all these amazing designs that my designers have locked up, and they look great, but maybe I want to get a better sense of how the app actually works from the end user's point of view. This is where having a prototype that I can play with can help validate my direction. Rather than asking a designer to wire one up, I can just ask Figma Make. All I have to do is copy this from Figma Design into Figma Make, paste it in. And with that, all the design context and the metadata that is in Figma Design is now in Figma Make. So let me add a prompt in the chat box to bring a bit more context. I'll ask Make to make this a fully interactive dashboard that matches this design one-to-one. Allow me to hover over the chart to see data and filter by time range.
One thing we've heard from customers is that they want the output they generate to look and feel consistent with their other products. With Figma Make, you can connect your design library and bring in style context like color pallets, and other core styling elements. This is an area we're investing a lot of time in. There is even more improvements to come.
All right. So now we're ready. We'll click here and Figma Make, as you can see, is starting to interpret the prompt, the designs we provided and even starting to write the code that will turn them into functional prototypes. You can see it begin to work. This will take a couple of minutes. So in the interest of time, let's take a look at a finished example. Here, you can see the working prototype that we got from the design and it's a single simple natural language prompt. And you can see it's fully interactive as I move my mouse around, my cursor and actually see the hover effects or toggle between these tabs. And if I want to make changes to generate output, I can simply prompt again. I can also easily refine my results by clicking here in order to select part of the prototype. For example, this new reminder button. And as I do that, I have the ability to change its color to something else should I want to and easily directly manipulate the output. Ola, there we go.
With Make, you can also edit, download or export the actual code behind the prototype. Figma Make also allows for multiplayer editing. So I can collaborate with my team in this code view and anyone in the file can also prompt their own changes alongside me. Okay. Now I have a working prototype for my fitness app that I can preview across screen sizes, share directly with my team for feedback, test with users or if I feel it's ready, publish directly to the web. This is still early days for Figma Make, and we're working hard to rapidly improve it. The response we've seen from users so far has just been amazing, and we're so energized for what's next. For example, Affirm is using Figma makes to help visualize and validate their ideas faster. Rather than writing detailed PRDs, product managers at Affirm use Make to create prototypes that everyone can interact with. This helps them work through their ideas faster.
Designers use Make at Affirm as a thought partner when they want to work through multiple concepts such as the user interaction pattern. Affirm's PMs, engineers and designers also use our Dev Mode MCP server, and they've told us it speeds up their development velocity by "orders of magnitude." One designer was able to rebuild major product flows in less than 2 days. Affirm also recently upgraded to an enterprise account. From building with Make to brand marketing in Figma Buzz to executive reviews with Figma Slides, Affirm uses the Figma platform company-wide.
Switching gears from Make. For some time now, our users have asked us to improve Figma's vector functionality. In this age of AI, where software is created faster than ever, it's an especially important moment for us to give our customers ways to be even more expressive on the Figma platform. We want to help our customers differentiate their product and their brand. They need to stand out from the crowd. So at Config, we launched Figma Draw, a set of tools optimized for visual design and freeform creation in Figma. Draw is part of our full seat and it became generally available in Q2. Let me hop into a quick demo so you can see how it works.
To use Figma Draw, all you need to do is go into a Figma Design file and click this toggle. Okay. Now I'm in Figma Draw. Draw offers 20-plus new tools like textures, effects and improved vector editing. But the real power of Figma Draw is the ability to bring more creativity and visual expression to your designs. I'm just going to show you a few of the features. You'll have to look at the rest yourself. I'll start with the sun illustration. It's a good start, but we can do more to bring this to life. One way to do it is with our repeaters feature. If I click here, you can see that as I move my mouse around, I can easily add more rays. And also, if I click the brush feature, then I can give a bit more texture with different brush strokes. I'll choose the noir one right here. What's also great about Figma Draw is you can use your existing design system. In that way, you're able to keep your illustrations on brand and avoid repetitive work.
For example, I've already defined a color palette here that works across a light mode and a dark mode of my app. So what I can do is I can take my component here, and I can copy and paste it into this new frame. When I do that, you'll notice that the colors update on that hand and basically the ground below the grass from black to white. That way, I don't have to go select those colors again from the start.
Our community has made some incredible things with Draw. And it's been amazing just to watch their creativity flourish, and some of them made things that we honestly didn't even think were possible. One example is from a community member, Erica Leong, a visual designer based in Canada. Erica uses Figma Draw in her role at our product and design agency as well as her freelance work. She can work and draw the riff on an illustration and then flip to Figma Design to do product design work, all without leaving the Figma platform.
And Inga Hampton, a brand designer and illustrator is pushing the boundaries of illustration in Figma, as you can see here. If I hover over her design in the different layers, you can see how complex her illustration is. She has layers representing freckles, interesting masking groups. It's quite impressive to see how these files are created. And of course, this is just a peek into what you can create with Figma Draw. Our community is always just so amazing in how they push our tools to the limit, and we're always excited to see where they take Figma next.
All right. Let's move on to Figma Sites. For years, our community and customers have had a simple request for us. They say, if we design in Figma, why can't I just press the publish button and go directly to the web. Well, now with Figma Sites, users can do that. They can create beautifully designed dynamic websites with custom code interactions powered by AI. We also offer animations, responsive layouts and more.
When it's time to ship, you can just hit that publish button. And just like that, you've got a live working website. You can even connect it to your own custom domain if you want to. We're very excited about what our users will be able to do with not just Figma Sites, but also our CMS offering that we have under development.
And finally, we announced Figma Buzz at Config. Buzz helps brand and marketing teams build assets at scale using the design teams libraries and brand graphics in Figma. When using Buzz, creatives and marketers can quickly customize everything from social media assets to event materials, you name it, at high volume with consistency. While Sites and Buzz are still in beta, we're thrilled by the responses that we've seen so far from the community. Our users can now go from design to build all the way to shipping a product or brand assets all in Figma.
And lastly, we continue to serve the evolving needs of developers who accounted for approximately 30% of our monthly active users during Q2. In Q2, we launched our Dev Mode MCP server. With Dev Mode MCP, developers can connect the design context and Figma to their AI coding tools. And with that, they can generate the base implementation of their front end at lightning speed. The combination of design context plus code-based context helps produce better code output from LLMs tailored to the users' designs. And it's been so exciting to hear how our customers are using us.
One customer example here is Coinbase, who serves users in more than 100 countries. Coinbase has been a Figma customer since 2018, and they've grown from just a few users, I remember when I went there and demoed in the first place, to hundreds of designers, developers, product managers, marketers and more, building multiple products from start to finish, all in Figma. And Coinbase ships fast. AI coding tools have helped and by implementing Figma's Dev Mode MCP server, Coinbase can make sure that LLM-generated code is design and formed. This means they can move quickly, but without sacrificing their brand or system integrity. Coinbase has seen encouraging early results with improved developer velocity, greater parity between design and development and a consistent user experience across our platform of products.
From the start, we've taken so much inspiration from Figma users and customers around the world. And of course, we're super focused on how we can keep meeting their needs. In Q2, we continue to make our product more accessible to customers outside the United States. In April, we localized our product and support for Korean language users. And then shortly afterwards in May, we made our product and support available in Brazilian Portuguese. We've seen this resonate with customers, including Itaú Unibanco and Nubank in the LatAm region.
Itaú is Latin America's largest private bank. With Figma's AI-powered platform, they've accelerated their product development process and the way teams work together across the company. Itaú Unibanco uses Figma to go from ideation to prototyping all the way to code and delivery, elevating the quality of their experiences that they deliver to customers.
Nubank is a fintech company that uses Figma Enterprise and serves more than 118 million customers. Figma's platform is where everyone works together in one space, including hundreds of designers, researchers, engineers and PMs. Figma has helped Nubank scale their buys with consistency and speed as they've grown across North and South America.
As I look ahead, I'm just so excited about the opportunity in front of us. The role of design and craft and the importance of building great user experiences has never been more critical. And this is especially true in a world where AI makes it easier than ever to build software. In this world, design is more essential and it's more powerful. Design is how companies win or lose. It is the critical differentiator. I want to thank our customers for their trust, our community for their energy and ideas and the entire Figma team for their hard work and incredible execution. We have so much more to build together, and I'm so looking forward to the future.
With that, I'll hand it over to our CFO, Praveer.
Thank you, Dylan. As Dylan mentioned, we are excited to share the results of another strong quarter. First, I want to reiterate our growth philosophy. We are focused on growing responsibly, which you can see in our multiyear track record of durable growth and non-GAAP operating margin profitability. We have been disciplined stewards of capital, and we'll continue to invest in the growth opportunities while managing our margins.
As Dylan said, we believe the opportunity ahead of us is large. We plan to deepen our investment in the near term to take advantage of this opportunity. We held our annual user conference, Config, during Q2 and it remains a key investment in our community, customer relationships and product momentum. When we introduce new products and features at Config, we often roll them out gradually to gather feedback and learn from early usage before we expand to broader availability.
This brings me to our Q2 results. As we laid out in our S-1, our rapid pace of innovation has been a consistent component of our growth algorithm, helping us win new customers and expand adoption within our existing customers as we meet their evolving needs. We rolled out updates to our pricing and packaging in March of this year. So Q2 is the first full quarter with the new pricing and packaging in place. Customers on annual plans will remain on our legacy plan until their first renewal. The customers who are on our monthly plan have all migrated to our new model.
We ended Q2 with $250 million in revenue, which is our best quarter yet. This represents 41% year-over-year revenue growth, fueled by an increase in new paid customers, renewals on our new pricing and packaging model and growth within our existing customers.
As we've expanded Figma's capabilities to serve more parts of the product development journey, we've seen the benefits of working on a unified platform resonate with more and more customers. During Q2, more than 80% of our customers use 2 or more products and 2/3 of our customers use 3 or more products. One example is Alaska Airlines. When Alaska Airlines and Hawaiian Airlines merged late last year, their design teams needed a way to work together while keeping each brand distinct. Both airlines were already using Figma. So when Alaska renewed their enterprise plan in Q2, they were able to bring their teams together seamlessly. Both brands now share design systems in a single secure account with built-in support for brand-specific libraries. With Variables, Dev Mode and Figma Make, the teams innovate faster and keep experiences consistent across every touch point, making it easier for millions of passengers to travel.
Our net dollar retention rate, which accounts for expansion, contraction and churn across paid customers who spend over $10,000 in ARR was 129% in Q2. Our net dollar retention rate was primarily driven by seat expansion within existing customers, along with renewals on our new pricing and packaging model. As of Q2, we now have over 11,900 paid customers spending over $10,000 in ARR and more than 1,100 paid customers spending over $100,000 in ARR, which grew 42% year-over-year.
Now to discuss some key income statement results. Unless otherwise noted, all metrics are non-GAAP. We've provided a reconciliation of GAAP to non-GAAP financials in our earnings release, which is posted to our website. Our gross margin this quarter was 90%. We anticipate that we will see further gross margin compression in the near term as we roll out our AI products, including Figma Make, and recognize increases in inference spend. This is the largest driver of the quarter-over-quarter change in our gross margin. We view this as an investment in our products, our product differentiation and meeting the evolving needs of our customers.
Our operating margin for Q2 was 5%. We see elevated sales and marketing spend in the quarter when Config takes place. If you look at our historical financials, you will see similar seasonality in Q2 2023 and Q2 2024. We decreased our sales and marketing costs as a percent of revenue year-over-year from 46% in Q2 2024 to 39% in Q2 2025. We also experienced a year-over-year increase in G&A costs as we invested in our public company readiness efforts.
Our adjusted free cash flow margin in Q2 was 24%. We saw year-over-year improvements in our adjusted free cash flow margin primarily due to strong collections growth, and we ended the quarter with $1.6 billion of cash, cash equivalents and marketable securities on our balance sheet. Within the $1.6 billion, we also held approximately $91 million in our Bitcoin exchange traded fund.
I also want to provide additional detail on our lock-up releases. First, as described in our S-1, current nonexecutive Figma employees may have the ability to sell up to 25% of their vested holdings after this earnings announcement, depending on the stock price.
Second, our early VC stockholders represent a large collective ownership position in the business, and we want to provide some new information around when their shares will be released from lock-up restrictions. Five of our largest VC stockholders have signed a new extended lock-up agreement with us. Their extended lock-up will expire approximately 1 year after the IPO with 17.5% of their shares being released after the Q3 2025 earnings, 20% after Q4 2025 earnings, 27.5% after Q1 2026 earnings and 35% after Q2 2026 earnings. When these shares are released, they may be held, transferred, distributed or sold at the discretion of the extended lock-up holders.
Additionally, Dylan has entered into a Rule 10b5-1 trading plan with a start date in November that will sell up to a maximum of 3.3% of Dylan's holdings, including all outstanding RSUs. For clarity, that does not include any shares that may be sold to cover tax withholding obligations in connection with the potential future settlement of RSUs. More details can be found in our 8-K and 10-Q that will be filed today.
Now let's close it out. As you may have seen in our earnings release, we intend to provide revenue guidance for both our current quarter and our annual outlook going forward. Today, our revenue base consists of seat-based subscriptions with the majority of our pro tier on monthly subscriptions and our org and enterprise tiers on annual subscriptions. We intend to complement the existing seat-based model with a consumption model meeting the needs of our evolving product platform. We also plan to provide annual guidance for operating income in the foreseeable future as we expect to have timely opportunities to reinvest throughout the year, meeting the needs of a rapidly evolving market.
Okay. Let's turn to guidance for the third quarter and full fiscal year. For the third quarter ending September 30, we expect revenue to be between $263 million and $265 million. As we previously discussed, our model is changing rapidly given the rollout of several new products in the quarter. While we have a proven track record of monetizing products and use cases on our platform, we are still early in understanding long-term adoption of our newer products. We will continue to learn more as we expand usage in Q3 and refine our pricing and packaging strategy. For the year, we anticipate that our revenue will be between $1.021 billion and $1.025 billion, implying 37% year-over-year growth at the midpoint.
Turning to operating income. We expect our full year operating income to be between $88 million and $98 million. We continue to explore ways that we can invest in our products and go-to-market support. We are willing to deepen this investment where we see strong returns. We are proud of the results that we have achieved, and we are even more excited about what is ahead for our customers, our community, our Figmates and our shareholders.
With that, we'll pass it back to the operator to open it up for questions.
[Operator Instructions] Our first question comes from the line of Elizabeth Porter with Morgan Stanley.
2. Question Answer
Great. Dylan, as you walked through earlier, Figma showed an accelerated pace of innovation and doubled the size of the product portfolio earlier this year. While understanding it's still early, just given the change in the scale of the portfolio and the areas that you're addressing, is there any context you could provide on how we should think about the ramp of new products or the monetization of new seat types maybe relative to prior product rollouts for Dev Mode or FigJam?
Thank you for the question and for being here. Yes. So for new products, I would say that, obviously, we're still early in the life cycle. These products are still quite young, and there's a lot of maturing to do. That said, we've been very excited by the initial engagement that we're seeing. For Figma Draw, we are covering a lot more of the use case than even I believed might be possible when we launched it. I mean we launched with 20-plus new features, which is very exciting. But the amount of expression that our users are able to do has been definitely extraordinary in my eyes. And we've been glad to see the usage as well.
For Figma Sites, we're seeing lots of use among freelancers and individuals who are creating websites directly in Figma, and they've always been wanting that publish button, so they can go directly to a live published site. And also, we're seeing usage amongst some enterprise customers as well.
And then for Figma Buzz, I would say that we're seeing demand across teams and also a lot of energy around this product. And this is one where we're getting extremely interesting feedback that is pulling us into thinking through new directions on the Buzz road map, and it's going to be very exciting to see how that plays out.
And finally, on Make, this is one where it's a big priority for us. And we're really excited about everything we can do here. We think there's an opportunity to differentiate that product in a way that's very Figma-specific, make it more interoperable with the rest of our platform and really give it a Figma spin that others have not seen with similar tools on the market. And I'll pass it to Praveer to speak more.
Yes. Yes. I appreciate the question and excited to be here. I think our approach to guidance here is we want to reflect what we know about the business with a high degree of confidence today. And as we've explained previously, our goal is to be as transparent as possible on what is being included there. And so as Dylan was sharing, we -- I mean, we doubled the product portfolio, rolled a number of these newer products out into beta post Config and GA-ed Make just recently in July.
And so from an understanding perspective, we're still early in that monetization journey and our understanding of how these products will perform. But from an investment perspective, we're not going to shy away from making deeper investments here in the near term in the form of broader sales and marketing pushes, investments in inference. We feel that there's a path here to strong returns over the medium to long term and get excited about the potential there.
Our next question comes from the line of Gabriela Borges with Goldman Sachs.
Congratulations to the team on the IPO. Dylan and Praveer, I wanted to stay on Figma Make for a moment. Maybe for Praveer, could you quantify or give us a little bit of directional color? Are you already seeing an uptick in the full seat? Did you see a change in trend because of Figma Make? And for Dylan, tell us a little bit about the competitive environment. You started alluding to it there at the end with being able to integrate into the broader suite of Figma to be able to differentiate yourself. To what extent is this still a greenfield opportunity? Are you having to convince customers that have already played around with other prototyping tools to move over? Maybe just a little bit of feedback from the field.
Yes. So I'm happy to start on the Make monetization side. And then if there's additional pieces that Dylan wants to speak to on the competition side, we can go there. So you're right in that we very quickly rolled out from beta to GA, and we're behind the scenes working to build out the billing infrastructure to support future monetization of the product. And today, what we've seen is we've broadened from providing usage on our full seat type now to being able to provide usage across all different personas and all different seat types, including our starter plan as we've gotten closer and closer to the GA moment there.
And so while we've a lot of different credits based on tier. So as a full user on our enterprise tier, you have a higher credit limit than the full user on our organizations tier. We're not strictly enforcing those limits today for full seats, but are enforcing those limits on other seat types. We plan on letting customers know that they have the opportunity to purchase additional AI credits in the future. And we plan to be intentional about how we transition folks to feel like they understand the model and can map the value that they're seeing with the value that's being received in the future.
Yes, I can take competition. There are a ton of other tools that are sort of in this vibe coding, vibe designing, vibe whatever you want to call it, area. And what makes Figma Make unique is the ability to take the design context from Figma into Make. And we believe that there's a lot more that we'll be able to do there in the future to make it so that you're able to create amazing results.
And also, we believe that the interoperability with the rest of Figma will set Make apart in a pretty significant way. So lots we're exploring there. And I think that in terms of customer feedback, we are excited to see just all the interest in Make overall, but also the engagement we're getting with customers and the time they're spending with us on this product. And I would say that the position we're in from a platform standpoint, I feel is to our advantage here.
Our next question comes from the line of Arjun Bhatia with William Blair.
Bear with me. I'm losing my voice. So hopefully, you can understand me. Dylan, maybe sticking on Make, I think one of the benefits of it or potential benefits of it is that it will attract different personas to create. And I'm curious what you're seeing in terms of which types of users are actually using Figma Make and is it expanding kind of your exposure to different personas across marketing, across product management and obviously, the core design persona as well.
Thank you for your question, and I hope you feel better soon. Thanks for making the time to call in. So for Figma Make and personas, I'd say that designers are obviously at our core for Figma. That said, we've seen a range of users get value out of Make. And we see it serving not just designers, but also developers, PMs, marketers, really the entire organization can get benefit here. And if we zoom out and kind of think about the core thesis that we talked about at the start of the call, our perspective has been for a long time now, a decade or so that design is a differentiator. And I think that in the age of AI, when software is easier to build than ever, that's even more so the case. And with that, you need to be able to lower the floor but also raise the ceiling, make it so that you're able to bring more people into the design process but also the raising the ceiling part is making it so that you can actually allow professionals to do even more with AI.
And the interesting thing about Make is that it sort of does both. It invites more people in to express their ideas and to share different perspectives on where you can take a product. But it also allows designers and professionals to go more high fidelity. And as we think about the AI functionality across our entire platform, I'm very excited about how we can continue to lower the floor and raise the ceiling. I think this is just the start.
Our next question comes from the line of Rishi Jaluria with RBC.
Wonderful. One common question that we got during the IPO process and post launching is maybe fast forwarding a little bit on the AI front. Obviously, Figma Make, great to see some of the early traction there. But if, in fact, AI ends up being a major paradigm shift and the nature of what we call "software shift" from prepackaged SaaS application to agents and multi-agentic systems. Can you maybe walk us through why you expect that Figma is still going to be not just relevant, but market-leading in that new paradigm in that new post-AI software world?
Yes. Thank you for the question and always down to talk about agents. It's a fun topic. I think that first of all, I'd say that the narrative around agents is not necessarily where I expect that will go with the world, but we'll see over time.
I think that right now, agents are being seen as this kind of black box that will take care of everything for you. And where I think it will end up is instead, you'll need to have way more surfaces that actually you expose through an agent in order to audit the work it's doing, but also you need to integrate agents into your software.
And I think that with agents and the surfaces that you have to design for them, they'll have different constraints than the software that you're designing otherwise. And this is just one example of sort of how much multiplication of screens and different targets that you need to design for. And I think that the role and the job of the designer will increase in complexity because of that multiplication of surface area. We're also going to see a lot more on different screen sizes, different modalities like VR and AR as well as, I suspect, different ways of interacting with screens in general. And I'm quite excited for that. I think our job for Figma is to make sure that whatever you're designing, we're able to support you. And so that's what we're focused on.
Our next question comes from the line of Michael Turrin with Wells Fargo.
Congrats to the team on making it this milestone. Dylan, you mentioned willing to take big swings just as part of the presentation. It's clearly been an amazing journey for Figma thus far. Maybe you and Praveer can speak to how you're thinking about use of cash given just the $1.6 billion you have on the balance sheet currently alongside any framework you're using to evaluate what would drive you to take one of those bigger swings going forward?
Thanks, Michael. I appreciate the question. I think you're right, we sit on $1.6 billion in cash. It gives us some flexibility here to invest in some of these new areas that we've been exploring both as we deepen our investments in AI with products like Figma Make in particular, and spend on the inference side as we evolve our sales and marketing presences and strategies there as we seek to take now a full suite and platform that out to market. And so we've got no shortage of ideas on how we can continue to refine our investment thesis internally, and we expect to pull those levers as we see fit.
I think the reason why we've settled on an annual guidance framework for operating margin is because we do believe we're going to find these opportunities throughout the year and want to have -- and want to be really clear that we intend to find those opportunities and really count on them at the right moment. And so expect to hear more from us on that in the future. And right now, we feel like we're well capitalized to be able to tackle the ideas that we've got on the table.
Yes. And I can add on the framework part. First of all, just reemphasize what Praveer said, which is that we're always scanning and looking at the landscape around us, both in ways that map to the current priorities of Figma as well as future directions we could go. And sometimes M&A for us is small scale. But we also, as I indicated in my founder letter, we're very willing to take big bets if we truly believe in them. And so it will be that framework for us to do that if we wanted to do M&A at scale. I think it would have to hit 3 criteria. The first is, of course, it has to be an amazing team and amazing asset in a way that we think it's a good setup for us to bring in.
The second characteristic I'd be looking at is they would need to be culturally consistent and hopefully actually additive to the culture, bringing new cultural traits that we want to get even stronger on.
The third is, I think that going forward, we would have to believe for M&A at scale that whatever we are bringing on maps to a company priority. That's one of our first or maybe second priorities, but not like a third. So if it's in the top 2 going forward, great. If not, it's probably not for us. I wouldn't limit our scanning and what we're looking at to things that are our current priorities. But in order to actually go forward, I would make sure that it maps to something that is a top priority. Of course, it's just the minimum, but that's the 3 points that I would want to meet at least. And again, we have a very high bar for [indiscernible] scale.
Our next question comes from the line of Alex Zukin with Wolfe Research.
Maybe I'll ask one on kind of pricing and packaging. Maybe just talk a little bit about how the conversations have gone with your enterprise customers with the new pricing and packaging rollout. Are you seeing anything different from what you initially expected, either positive or negative? And any way to think about the growth contribution from pricing and packaging for the rest of the year based on how the quarter played out?
Alex, I really appreciate the question. And I think let me first recap some of the changes that we made in the early part of March of this year. So one, we introduced the concept of a multiproduct seat, giving more functionality to each user. Second, we changed the admin upgrade experience, effectively empowering our admins to have explicit approval authority prior to a new user being provisioned. And lastly, we increased the price of our full user seat type. In some cases, our customers may see that their spend is increasing with us. In other cases, customers won't actually see any price change. And there are cases here where monthly prices will actually go down for a particular customer cohort.
And we recognize that as we roll through some of these changes, and we've now had an opportunity to see many of these changes through a few renewal cadences on our pro business, which is majority monthly. We see an initial sort of seat remapping as users are -- or rather as teams are transitioning and post that, they end up in a much more predictable expansion pattern.
And then on the org and enterprise side, which are annual in nature and contracts, while also we sell an annual subscription for parts of our pro tier, we're still phasing in through some of those renewals there. And so we just completed our first quarter where we've seen that full transition for companies that were going through those initial renewal moments.
And while we aren't commenting on the quarterly impact, we do estimate that we'll have a mid- to high single-digit tailwind to growth this year due to the changes that we've rolled out.
Our next question comes from the line of Brad Sills with Bank of America.
I wanted to ask a question about agents and some of the agentic features, really an impressive array of new features that you've launched throughout the different offerings. I wondered if there's any pattern recognition that you're seeing here with regards to usage, engagement, adoption. Any themes or trends that you've noticed that maybe stand out to you with regard to usage of those features?
Yes. Thank you for the question. I would say that we are still early, especially in the sense that we have so many ideas of how we can improve our AI functionality as well as add additional AI functionality across our entire platform. And I think that the sort of distribution of usage that we see now while it's showing good amounts of activity will be fundamentally different as we go forward and probably not in ways that we can fully predict. And so we're watching that carefully and making sure we can learn as much as possible from it.
Our next question comes from the line of Brent Bracelin with Piper Sandler.
Dylan, I'm trying to understand the Figma Make opportunity. I was hoping you could maybe help size the prototyping market that it addresses. If I go back and look at Figma Design, clearly disrupted the single-player design tools out there. Figma Dev Mode really expanded the user base outside of design into the developers. And what does Figma Make bring? Is this a new user base? Do you think this is going to increase ARPU by cross-selling in the installed base? Walk us through the AI prototyping opportunity and what Figma Make brings there.
Sure. I'd say that, first of all, I don't see Figma Make as just prototyping. I see it as a way to prototype as well, but also you can go from prompts to working app and actually ship what you have. I think that in terms of personas, what I believe we will see in the long term is expansion of the personas that are doing more complex editing tasks on the Figma platform and creation tasks. And if you think about it, again, if design is a differentiator, it's how you win or lose.
If you accept that as the premise in this age of AI and easy to build software, then I think you really want to make sure that great ideas are coming from everywhere. And also, I think it's very important to be in a world where you have all the context that you need, not only the context from your visuals or your user flows or your brand, but also culture, business constraints and insights across your organization. Figma Make opens up that opportunity for more people to contribute to the design process.
I also think that if you conceptualize design as this branching path where you're looking at a full option space and trying to figure out which of the branches to go down, Figma Make helps you really explore that option space faster and get to an insight around where you want to go deeper on so that you can add your own craft as a human. You can add your own point of view. We can help with that through Figma Make in order to help designers but also everyone else in the organization accelerate ideas further and designers can help lead that transformation.
Ladies and gentlemen, that concludes today's call. Thank you all for joining. You may now disconnect.
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Figma — Q2 2025 Earnings Call
Figma — Q2 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $250 Mio (neues Quartalsrekord; +41% YoY)
- Netto‑Dollar‑Retention: 129% (NDR; misst Umsatzentwicklung bestehender Kunden inkl. Expansion/Churn)
- Non‑GAAP Betriebsmarge: 5% (ohne Aktiendelikationsaufwand)
- Adj. FCF‑Marge: 24% (adjusted Free Cash Flow‑Marge)
- Cashbestand: $1,6 Mrd (inkl. ≈$91 Mio in Bitcoin‑ETF)
🎯 Was das Management sagt
- Plattformfokus: Ziel ist ein einheitliches, AI‑gestütztes Produkt‑Ökosystem für Design bis Auslieferung; Design als Differenzierer.
- Produktoffensive: Auf Konferenz Config vier neue Produkte gelauncht (Make, Draw, Sites, Buzz) plus Übernahmen (Modyfi, Payload).
- Investitionswillen: Starkes Near‑Term‑Investment in KI (Inference‑Kosten) und Go‑to‑Market; Bereitschaft für größere M&A‑"Swings".
🔭 Ausblick & Guidance
- Q3‑Guidance: Umsatz erwartet $263–265 Mio.
- Jahres‑Outlook: Umsatz $1,021–1,025 Mrd (≈37% YoY am Midpoint); operatives Ergebnis $88–98 Mio.
- Risiko‑Hinweis: Erwartete Margenkompression durch KI/Inference‑Aufwand; Management plant zusätzliches Deployen von Konsummodellen.
❓ Fragen der Analysten
- Monetisierung von Make: Management beschreibt frühe starke Nutzung, arbeitet an Billing/AI‑Credits; konkrete Umsatzpfade noch unbestimmt.
- Pricing‑Effekt: Neue Preis‑/Packaging‑Rollouts liefern einen mittleren bis hohen einstelligen Wachstums‑Tailwind, aber gestaffelte Wirkung über Erneuerungen.
- Kapital & Lock‑ups: $1,6 Mrd Kasse ermöglicht Investments; gestaffelte VC‑Lock‑up‑Releases und 10b5‑1‑Plan des CEO sind zu beobachten (Verkaufsdruck‑Risiko).
⚡ Bottom Line
- Fazit: Starkes Wachstum bei Profitabilität auf Non‑GAAP‑Basis; Figma investiert aggressiv in KI und neue Produktkategorien, was kurzfristig Margen belastet, langfristig aber ARPU‑ und Plattformchancen eröffnen kann. Wichtige Beobachtungspunkte: Monetisierung von Figma Make, Margenentwicklung (Inference‑Kosten) und bevorstehende Lock‑up‑Releases.
Finanzdaten von Figma
Umsatz
Der Umsatz stellt die Summe aller Einnahmen eines Unternehmens z. B. für dessen Produkte oder Dienstleistungen dar.
Umsatz (TTM) einfach erklärtDirekte Kosten
Direkte Kosten sind die Kosten, die direkt im Zusammenhang mit der Herstellung des Produkts oder der Dienstleistung entstehen.
Bruttoertrag
Der Bruttoertrag gibt an, wie viel vom Umsatz nach Abzug der direkten Herstellkosten im Unternehmen verbleibt. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der Bruttomarge (engl. Gross Margin).
Brutto Marge einfach erklärtVertriebs- und Verwaltungskosten
Die Vertriebs- & Verwaltungskosten (engl. Selling, General & Administrative expenses, kurz SG&A) beinhalten alle Aufwände für Marketing und den Verkauf sowie die allgemeine Verwaltung des Unternehmens.
Forschungs- und Entwicklungskosten
Die Forschungs- und Entwicklungskosten (engl. research & development costs, kurz R&D) geben Auskunft darüber, wie viel das Unternehmen in die Forschung und die Entwicklung seiner Produkte investiert. Vor allem prozentual vom Umsatz und im Vergleich zu direkten Wettbewerbern sind die Kosten interessant.
EBITDA
Das EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) ist der Gewinn des Unternehmens vor Zinsen, Steuern und Abschreibungen. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der EBITDA-Marge.
Abschreibungen
Abschreibungen stellen Wertminderungen von Vermögensgegenständen des Unternehmens dar (z.B. durch Abnutzung von Maschinen).
EBIT (Operatives Ergebnis)
Das EBIT (engl. Earnings Before Interest and Taxes) ist der Gewinn des Unternehmens vor Zinsen und Steuern, das auch als operatives Ergebnis bezeichnet wird. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von
der EBIT-Marge.
Nettogewinn
Der Nettogewinn stellt den Gewinn oder Verlust nach Abzug aller Kosten dar.
Nettogewinn einfach erklärtaktien.guide Premium
| Jun '26 |
+/-
%
|
||
| Umsatz | 1.281 1.281 |
43 %
43 %
100 %
|
|
| - Direkte Kosten | 267 267 |
225 %
225 %
21 %
|
|
| Bruttoertrag | 1.014 1.014 |
136 %
136 %
79 %
|
|
| - Vertriebs- und Verwaltungskosten | 1.384 1.384 |
208 %
208 %
108 %
|
|
| - Forschungs- und Entwicklungskosten | 1.217 1.217 |
696 %
696 %
95 %
|
|
| EBITDA | -1.566 -1.566 |
2.822 %
2.822 %
-122 %
|
|
| - Abschreibungen | 21 21 |
94 %
94 %
2 %
|
|
| EBIT (Operatives Ergebnis) EBIT | -1.587 -1.587 |
3.489 %
3.489 %
-124 %
|
|
| Nettogewinn | -1.578 -1.578 |
16.782 %
16.782 %
-123 %
|
|
Angaben in Millionen USD.
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Firmenprofil
Figma Inc ist ein US-amerikanisches Unternehmen, das in der Softwarebranche tätig ist. Figma, Inc. entwirft und entwickelt Plattformen für Menschen, die gemeinsam digitale Produkte entwickeln. Das Unternehmen hilft funktionsübergreifenden Teams, sich abzustimmen und Software effizienter zu erstellen, und gewährleistet den fortschrittlichen Zugang und die Kontrolle, die große Unternehmen benötigen. Zu den Produkten gehören Figma Design, Dev Mode, Figma Sites, Figma Make, Figma Draw, Figma Buzz, FigJam und Figma Slides. Figma Sites ist ein Produkt, mit dem Kunden eine Website entwerfen und direkt im Internet veröffentlichen können, mit einer benutzerdefinierten URL. Figma Make ist ein KI-gestütztes Werkzeug, das eine Eingabeaufforderung in einen voll funktionsfähigen Prototyp verwandelt. Figma Buzz ist ein Produkt zur einfachen Erstellung von Marketing-Assets (z. B. Social Media Assets und digitale Anzeigen) in einem Umfang, der mit der Marke oder der visuellen Identität übereinstimmt. Figma Draw bietet einen Raum für die feinere Vektorbearbeitung, die beim Zeichnen detaillierter Ikonografie und Produktillustrationen erforderlich ist. Figma Design kombiniert leistungsstarke Funktionen mit einem kollaborativen Arbeitsbereich, damit Teams gemeinsam bessere Produkte entwerfen und erstellen können.
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| Hauptsitz | USA |
| CEO | Mr. Field |
| Mitarbeiter | 1.886 |
| Webseite | www.figma.com |


