OpenAI’s adjusted operating margin narrowed to -109% in the third quarter from -150% in the second, Bloomberg reported, according to TechCrunch and Quartz. That is about $1.09 of adjusted operating loss for each dollar of revenue, down from about $1.50, by our arithmetic.
Revenue rose to $10 billion from $6.7 billion. On the reported margins, the implied adjusted loss rose by about $0.85 billion while revenue rose by $3.3 billion, or about 26 cents of added loss per added dollar of revenue, by our arithmetic.
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The key insight:OpenAI‘s adjusted operating margin narrowed to -109% in the third quarter from -150% in the second, Bloomberg reported, according to TechCrunch and Quartz: about $1.09 of adjusted operating loss per revenue dollar, down from about $1.50, by our arithmetic. Revenue rose $3.3 billion while the implied loss rose about $0.85 billion, or about 26 cents of added loss per added dollar, by our arithmetic.
Bloomberg reported that OpenAI’s “revenue increased nearly 50% from the prior quarter and almost threefold from the same period a year earlier”, citing people familiar with the matter. “The financial details were shared with investors during a call on Tuesday”, it said, naming OpenAI President Greg Brockman and Chief Financial Officer Sarah Friar among the speakers.
Quartz, citing Bloomberg, wrote that “OpenAI’s adjusted operating margin stood at -109% in the third quarter, a smaller loss than the -150% recorded in the second quarter”. It added that OpenAI told investors its annualized revenue stood at roughly $50 billion at the end of September. OpenAI declined to comment, according to Bloomberg’s report as syndicated by The Business Times.
OpenAI’s quarterly revenue and implied adjusted operating loss, second and third quarters of 2026. Revenue and adjusted operating margins (-150% and -109%) as reported by Bloomberg, relayed by TechCrunch and Quartz; the loss bars are margin times revenue, our arithmetic. OpenAI is private and does not file its results.
The Loss per Dollar, Quarter by Quarter
A margin of -150% means about $1.50 of adjusted operating loss for each dollar of revenue; -109% means about $1.09. The gap is 41 cents, or 27.3% less per dollar, by our arithmetic.
Applied to the reported revenue, the margins imply an adjusted operating loss of about $10.05 billion in the second quarter and about $10.9 billion in the third, by our arithmetic. The Wall Street Journal reported a $10.9 billion operating loss for the third quarter, as we reported.
So the loss in dollars still grew, by about $0.85 billion, while revenue grew by $3.3 billion, or 49.3%. Each added dollar of revenue came with about 26 cents of added adjusted loss, against $1.50 per dollar across the second quarter, by our arithmetic.
Against Anthropic’s Filed Quarter
Anthropic’s S-1/A reports an operating loss of $567 million on revenue of $16,956 million for the three months to 30 September, or 3.3% of revenue by our arithmetic. That is a GAAP operating figure, not an adjusted one, so it is not a like-for-like comparison with OpenAI’s reported margin. Anthropic’s quarterly revenue was 1.7 times OpenAI’s, as we calculated.
On run rates, TechCrunch noted that Anthropic said its annual revenue run rate reached $81 billion at the end of October, against roughly $50 billion for OpenAI at the end of September, and that the two companies “calculate their annualized revenue differently”. Those are annualised rates, not quarterly revenue.
The Structural Read
As we read it, the reported numbers describe a business whose new revenue is far less loss-making than its existing base: the loss per dollar fell 27.3% in one quarter, by our arithmetic, while the loss in dollars still rose. Whether that continues depends on costs the reports do not break out, and the adjusted measure’s exclusions are not stated.
Quartz, citing Bloomberg, 11 Nov 2026
“OpenAI’s adjusted operating margin stood at -109% in the third quarter, a smaller loss than the -150% recorded in the second quarter”
Three Implications
FOR OPENAI’S INVESTORS The figures were shared with investors on a call on 10 November, Bloomberg reported, with revenue up nearly 50% on the quarter and almost threefold on the year.
FOR THE COMPARISON WITH ANTHROPIC Anthropic’s S-1/A shows a $567 million operating loss on $16,956 million of revenue, a GAAP figure, not an adjusted one.
FOR RUN RATES TechCrunch noted the two companies calculate annualized revenue differently, so the $50 billion and $81 billion run rates are not like for like.
The framework argues that “The negative margin is not a leak. It is a procurement budget.”
As we read it, OpenAI’s reported quarter puts a number on that budget: about $1.09 spent beyond each revenue dollar, down from about $1.50. The framework was written about subscription plans in June and does not discuss these figures.
What Is Not Established
We read Bloomberg’s first two paragraphs and its syndicated short version; the margin figures come from the full article as relayed by TechCrunch and Quartz. The reports do not say which costs the adjusted measure excludes. OpenAI is private and does not file its results; the figures were shared with investors and reported by people familiar with them. The implied loss figures are our arithmetic from reported, rounded margins.
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Bloomberg reported that OpenAI’s adjusted operating margin narrowed to -109% in the third quarter from -150%, on revenue of $10 billion against $6.7 billion. By our arithmetic, the loss per revenue dollar fell to about $1.09 from about $1.50, while the implied loss in dollars rose by about $0.85 billion.
A note on sourcing. We read the opening of Bloomberg’s report and its syndicated version in The Business Times; the margin and run-rate figures come from Bloomberg’s report as relayed by TechCrunch and Quartz, which we read in full. Anthropic’s figures come from its S-1/A filed with the SEC on 10 November 2026. Per-dollar figures, implied losses and ratios are our arithmetic.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
