A short explainer on run-rate revenue. It teaches the general idea only and does not discuss either company.
The key insight: As we read the disclosures, the two labs now carry marks within reach of each other, near $1.25 trillion, but only Anthropic has filed a revenue figure, so only its multiple can be computed: about 18.4 times annualised third-quarter revenue at $1.25 trillion, by our arithmetic.
OpenAI’s $1.25 trillion is 46.7% above the $852 billion post-money valuation of the round it closed on 31 March, by our arithmetic. Bloomberg said the funding was wired as of Friday and that the round could reach $20 billion; the $11 billion closed so far is 55% of that, by our arithmetic.
For Anthropic, the $1.25 trillion midpoint of buyers’ reported range is 29.5% above the $965 billion post-money valuation of its Series H round in May, by our arithmetic. Some potential buyers were reported to go as low as $1.1 trillion. The Financial Times reported that Anthropic is pressing ahead with a $1.5 trillion target and a listing before Thanksgiving, a level 55.4% above the May round, by our arithmetic.
Each lab’s last disclosed round against the mark reported on 6 November 2026, in $ billions: OpenAI’s $852 billion (31 March) and the $1.25 trillion round Bloomberg reported; Anthropic’s $965 billion Series H (May), the $1.25 trillion midpoint of buyers’ reported $1.2 trillion to $1.3 trillion talk and the $1.5 trillion target the FT reported. Midpoint and comparisons are our arithmetic.
Revenue: What Each Has Disclosed
Anthropic’s S-1/A gives revenue of $33,242 million for the first nine months of 2026 and $17.0 billion for the third quarter, with a gross margin of 85.5% by our arithmetic and an Adjusted Operating Margin of 12%, a non-GAAP measure.
OpenAI has not filed financialstatements. Its executives have given growth rates, not revenue totals. President Greg Brockman cited “70% quarterly growth in our annualized revenue” in the third quarter, and CFO Sarah Friar told CNBC, according to our machine transcript of a clip, “Our business grew 70% quarter over quarter”. Neither figure is filed with a regulator, and neither gives a dollar base.
The Multiple We Can Compute
Annualising Anthropic’s $17.0 billion third quarter gives $68.0 billion. Against that, $1.1 trillion is 16.2 times, $1.25 trillion is 18.4 times and $1.5 trillion is 22.1 times, all by our arithmetic. An annualised quarter is not a forecast, and it ignores growth or decline after September.
The same multiple cannot be computed for OpenAI from disclosed figures, because OpenAI has not published a revenue total for the quarter. Any OpenAIprice-to-sales figure would rest on estimates we have not verified.
Capital Raised
OpenAI’s March round brought $122 billion in committed capital, according to the company. Techmeme’s summary of the reporting, citing sources, puts Anthropic’s planned IPO raise at $80 billion to $100 billion, which would be 5.3% to 6.7% of a $1.5 trillion valuation, by our arithmetic.
What we can’t compare.OpenAI’s revenue total, margins and losses are not public, so its valuation multiple, gross margin and cash burn cannot be set against Anthropic’s. Bloomberg’s report does not say whether $1.25 trillion is pre-money or post-money. Anthropic’s valuation is not yet a price: the $1.2 trillion to $1.3 trillion talk and the $1.5 trillion target are reported, not filed.
As we read the rounds, OpenAI’s reported mark is 46.7% above its $852 billion March post-money, and the midpoint of Anthropic’s buyer talk is 29.5% above its $965 billion May round, by our arithmetic.
As we read the revenue lines, Anthropic’s filing gives a dollar base of $17.0 billion for the third quarter, while OpenAI’s executives gave growth rates of 70% without a dollar base.
As we read the markets, Anthropic has prediction-market and pre-IPO perpetual prices in our reporting, and OpenAI has none that we report.
Bloomberg, 6 Nov 2026, on OpenAI
“values the company at $1.25 trillion”
Three Implications
FOR INVESTORS A buyer can price Anthropic against filed revenue; for OpenAI, our reporting has a round price but no filed revenue total.
FOR THE IPO The FT reported a $1.5 trillion target, which would be about 22.1 times annualised third-quarter revenue, by our arithmetic.
FOR OPENAI Bloomberg reported that the round could increase to as much as $20 billion in total.
The analysis says: “AI exhibits genuine bubble characteristics — excessive hype, overvaluation, capex commitments that exceed the unit economics of any single application — at the same time as it exhibits genuine supercycle characteristics — real productivity gains, fundamental restructuring of profit pools, civilizational impact.”
As we read it, two marks near $1.25 trillion are one data point on that tension; the analysis does not discuss these rounds.
What Is Not Established
We have read only the readable opening of Bloomberg’s report and Techmeme’s summary of the Anthropic reporting, not the full articles. Anthropic’s IPO has not priced. All percentages and multiples here are our arithmetic, not figures either company states.
This Week In The AI Supercycle
Anthropic’s Reality Check, The Capital Squeeze, & The New World Order
This week’s issue: for two years the AI build-out was priced as a growthstory. This week it started being priced as a credit story.
OpenAI’s round and Anthropic’s IPO talk both sit near $1.25 trillion, 46.7% and 29.5% above their last rounds by our arithmetic, but only Anthropic has filed revenue: $17.0 billion in the third quarter, about 18.4 times annualised at that mark.
A note on sourcing. Anthropic’s revenue and margin figures are from its S-1/A of 2 November 2026. OpenAI’s round is from Bloomberg’s report of 6 November and OpenAI’s 31 March post. Anthropic valuation talk, the FT target, market prices and executive quotes are from our earlier pieces, linked above; the Friar quote is from our machine transcript of a CNBC clip. All percentages and multiples 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.
