A post on X by the Milk Road AI account on 23 October 2026 said $650 billion had been wiped off the proposed valuations of Anthropic and OpenAI: $500 billion at Anthropic, from about $2 trillion to about $1.5 trillion, and $150 billion at OpenAI, from $1.4 trillion to $1.25 trillion. We checked each number against the reports behind it.
The Anthropic figures match a Reuters report of 15 October on investors’ IPO expectations. The OpenAI figures match the Financial Times’ posts on X of 22 October on OpenAI’s private-round target; CNBC reported the same $1.25 trillion as a pre-money valuation.
Business Pill · RUN-RATE REVENUE
A short Business Engineer explainer of run-rate revenue: what an AI company’s annualized number means. It teaches the general idea only and says nothing about the figures in this piece.
The key insight: As we read it, the $650 billion is two different gaps added together: about $500 billion between IPO expectations for Anthropic in one Reuters report, and $150 billion between OpenAI’s $1.4tn pitch and $1.25tn target in the FT’s posts.
Anthropic. Reuters reported on 15 October 2026, citing people familiar with the matter, that some investors who attended Anthropic’s investor day discussed a valuation of around $1.5 trillion, which Reuters called “a significant step down from the roughly $2 trillion valuation that investors had previously expected for the November share sale.”
OpenAI, the cut. In posts on X on 22 October 2026, the FT reported that OpenAI has trimmed its valuation target to $1.25tn after pitching a higher price, and that the AI lab floated a $1.4tn price tag to investors earlier this month, according to documents seen by the FT.
OpenAI, the round. CNBC reported on 22 October 2026 that OpenAI was close to finalizing a round of up to $30 billion at a $1.25 trillion pre-money valuation. Reuters had reported on 19 October that a round of about $30 billion could valueOpenAI at over $1.4 trillion.
The Information, 23 October. In a post on X, The Information wrote that “OpenAI trimmed its valuation target to $1.25T after investor pushback.”
Valuation figures for Anthropic and OpenAI, earlier vs later: about $2 trillion previously expected for Anthropic’s IPO and around $1.5 trillion discussed by some investors (Reuters, 15 Oct 2026); over $1.4 trillion for OpenAI (Reuters, 19 Oct 2026) and $1.25 trillion pre-money (CNBC, 22 Oct 2026). The gaps are our arithmetic.Valuation figures, earlier vs later: Anthropic about $2 trillion previously expected and around $1.5 trillion discussed by some investors (Reuters, 15 Oct 2026); OpenAI a $1.4tn price tag floated to investors and a $1.25tn trimmed target (FT posts on X, 22 Oct 2026). Approximate figures as reported.
What Was Posted on X
AI’s two biggest frontier labs just saw $650 BILLION wiped off their proposed valuations, and I actually think this is a GOOD thing.
Anthropic was previously expected to go public at around a $2 trillion valuation, but investors are now discussing something closer to $1.5 trillion. That’s a $500 billion reduction, or 25%. Meanwhile, OpenAI was initially targeting a $1.4 trillion valuation for its latest funding round, but that number has now dropped to $1.25 trillion, another $150 billion reduction.
I’ve said this before, but I think frontier AI labs are way too expensive right now. I’m extremely bullish on AI and believe we’re going through one of the greatest technological transformations in human history. But that doesn’t mean every company developing these models deserves a trillion dollar valuation. These businesses are growing incredibly fast, but they’re also spending enormous amounts of money on compute, infrastructure, talent, and training increasingly sophisticated models. Competition is intensifying and investors are starting to question how much of that revenue will eventually translate into sustainable profits.
And I think that’s a healthy development. For the longest time, investors were willing to throw money at practically anything associated with AI without seriously questioning valuations. Now we’re finally seeing some discipline return. Lower valuations don’t mean AI demand is disappearing. They mean investors are becoming more selective about what they’re willing to pay for future growth. I actually think this is GOOD for the long-term health of the AI industry. We need capital flowing toward companies that can generate real returns, not just companies with the biggest growth projections.
I’m still incredibly bullish on AI infrastructure, particularly memory, photonics, semiconductors, and power. Those are the areas where I continue to see some of the most interesting opportunities. AI can completely change the world while some of today’s biggest AI companies still turn out to be overpriced. Both things can be true.
Milk Road AI wrote on X that $650 billion had been wiped off the proposed valuations of Anthropic and OpenAI, $500 billion and $150 billion, and called it a good thing. The figures and the view are the poster’s own; the piece checks the numbers against the reports.
The Numbers, Side by Side
The table sets each earlier figure against the later one, with the outlet and date for each. The gaps are our arithmetic.
Lab
Earlier figure
Later figure
Gap (our arithmetic)
Same basis?
Anthropic (IPO)
About $2T previously expected (Reuters, 15 Oct)
Around $1.5T discussed by some investors (Reuters, 15 Oct)
About $500B, or 25%
Both are investor expectations in one report; no price has been set
OpenAI (private round)
$1.4tn price tag floated to investors (FT, 22 Oct)
$1.25tn trimmed target (FT, 22 Oct); $1.25T pre-money per CNBC
$150B, or about 11%
Both are OpenAI round targets in the FT’s posts; adding up to $30B of new money to CNBC’s pre-money figure gives up to about $1.28T
Sources: Reuters, 15 October 2026; the FT’s posts on X and CNBC, 22 October 2026, as covered in our earlier pieces. Gaps and percentages are our arithmetic.
The $650 billion in the post is the sum of the two gaps, $500 billion and $150 billion. It adds an expected IPO value at one company to a private-round valuation at the other, two different measures.
What Was Posted on X
The Milk Road AI post calls the lower valuations “a GOOD thing” and says frontier AI labs are “way too expensive right now.” Those are the poster’s own views. The Information’s post on OpenAI was a reader poll with four options, from “Healthy price discipline” to “Still absurdly high, nothing has changed.”
Connecting the Coverage
Our Anthropic valuation piece covered the Reuters report of 15 October in full. Our OpenAI round piece covered the Reuters report of 19 October and the CNBC and FT reports of 22 October. Our Damodaran piece covered Aswath Damodaran’s table, which puts a $1.5 trillion Anthropic at 23.08 times the $65 billion run rate he lists and a $2 trillion one at 30.77 times. Our AI selloff piece covered the market moves of 22 October. What’s new: the post’s $650 billion adds the Reuters gap and the FT gap into one figure.
The Structural Read
As we read it, the Anthropic half is an expectation, not a price: Reuters reported what some investors discussed at an investor day, and no IPO price has been set.
As we read it, the OpenAI half is a private-round target: the FT reported a $1.4tn price tag floated to investors and a $1.25tn target, which CNBC reported as a pre-money valuation.
As we read it, the yardstick matters too: Damodaran’s table puts a $1.5 trillion Anthropic at 23.08 times the $65 billion run rate he lists, and a $2 trillion one at 30.77 times.
Reuters, 15 October 2026
“a significant step down from the roughly $2 trillion valuation that investors had previously expected for the November share sale”
Three Implications
FOR IPO BUYERS Reuters reported that around $1.5 trillion was discussed by some investors; Anthropic has not set a price.
FOR OPENAI’S ROUND CNBC reported a round of up to $30 billion at a $1.25 trillion pre-money valuation; adding the new money gives up to about $1.28 trillion, by our arithmetic.
FOR READING THE $650 BILLION The figure sums an IPO expectation gap and a private-round target gap, as the table above shows.
The framework describes its subject as “How the money flows, where it cracks, what it buys, who can absorb it”.
As we read it, the valuation figures are the top of that chain: what investors will pay for the two labs sets how much more capital they can raise for compute. The framework was published in May 2026 and does not discuss these reports.
What Is Not Established
Anthropic has not set an IPO price, and the $1.5 trillion and $2 trillion figures are what investors discussed or expected, according to Reuters’ sources. OpenAI’s round figures rest on the FT’s documents and people familiar with the matter, and on CNBC’s unnamed sources. Whether the FT’s $1.4tn was a pre-money or post-money figure is not stated in our coverage of it. We did not contact Anthropic, OpenAI or Milk Road.
Business Engineer Framework
The AI Capex Map & The State of AI Hyperscalers
A Business Engineer map of how the AI build-out is financed and what happens if revenue lags it.
The Anthropic half of the $650 billion matches Reuters’ two figures, about $2 trillion expected and around $1.5 trillion discussed. The OpenAI half matches the FT’s $1.4tn pitch and $1.25tn target. The total adds an IPO expectation at Anthropic to a private-round target at OpenAI.
A note on sourcing. This piece checks a 23 October 2026 post by Milk Road AI on X against Reuters’ report of 15 October and the FT’s and CNBC’s reports of 22 October, as covered in our earlier pieces. We could not read the FT article itself; its figures are from the FT’s posts on X. The outlets’ figures rest on documents and unnamed sources. The gaps are our arithmetic. We did not contact Anthropic, OpenAI or Milk Road.
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.
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