OpenAI Funding Shrinks by One-Third, Anthropic Valuation Falls Below $1.5 Trillion from $2 Trillion: AI Private Market Enters a Repricing Cycle

In early November 2026, OpenAI and Anthropic both proactively lowered their valuation expectations within the same week. This is not an isolated misstep by one company, but the first clear signal that the entire private market is repricing the AI narrative.

Both Companies Cut Valuations in Tandem: What the Numbers Say

According to technology funding outlet TechFundingNews, the first close of OpenAI’s new funding round was completed in early November, with approximately $11 billion received and a locked valuation of $1.25 trillion. That is below OpenAI’s original target set a month earlier: a $1.4 trillion valuation and a $30 billion funding size. The first $11 billion tranche is only one-third of the original plan, and the cap for the entire round has been compressed to $20 billion. To fill the institutional subscription gap, OpenAI also worked with investment banks to include high-net-worth individual investors in the subscription list.

Anthropic’s situation is even more direct. According to Bloomberg, during pre-IPO roadshow meetings from late October to early November, institutional investors pressured Anthropic and pushed its valuation target down from a range of up to $2 trillion to about $1.404 trillion to $1.5 trillion. Calculated from the high point, Anthropic’s valuation evaporated by more than $600 billion within weeks. According to Fortune, some market participants believe Anthropic’s proactive choice of a lower valuation is a “wise strategy” to ensure its share price does not fall below the issue price after the IPO; but more analysts see it as investors using actual bids to question the AI industry narrative.

If Anthropic lists smoothly and its share price rises, the AI industry will continue “business as usual”; otherwise, “some companies will face bankruptcy risk.” — Comment from a market analyst, according to Futunn

Not Accidental: Market Pricing Logic Is Shifting

Over the past three years, the valuation logic of large-model AI companies has rested on one premise: rapid leaps in model capability will translate into quantifiable commercial revenue within a short cycle. This logic supported the ever-rising funding multiples since ChatGPT’s release and made “stronger models, higher valuations” the market’s default narrative.

But now, the capital market is asking a question that had previously been set aside: how much of the capability gap on model leaderboards has actually been converted into real commercial value?

The two companies’ valuation cuts came after the same round of sell-offs in publicly traded AI-related assets. This is no coincidence—repricing in the public market is a leading signal of adjustments to private-market valuation logic. When AI concept stocks face selling pressure, institutional investors naturally tighten their bids at the private level. According to Bloomberg, Howard Morgan, co-founder of B Capital, has advised several AI startups to proactively lower their funding valuations, and revenue multiples for AI startups have generally tightened over the past two weeks.

The deeper contradiction lies in the capital expenditure structure. OpenAI CFO Sarah Friar has publicly stated that the company will continue to increase investment in AI infrastructure, covering data centers, chips, and power facilities. This means the capital consumption curve is steep and rigid—training stronger models and maintaining a larger user base each require large upfront hardware spending. Yet the contraction in funding size is occurring precisely at a time when the capex bill is getting longer.

The “Arms Race” Narrative Meets Its First Capital Test

Over the past two years, the “model arms race” has been the AI industry’s most widely circulated narrative framework: GPT-4 versus Claude 3, o1 versus Gemini, with each release accompanied by claims of capability leaps. The commercial core of this narrative is: whoever moves faster and builds stronger models can capture a larger market share and thus support a higher valuation.

However, this synchronized downward revision exposes a structural flaw in that narrative: there is a time lag between the pace of model capability improvement and the pace of commercialization. OpenAI and Anthropic are both globally recognized top model companies, and their technical capabilities are beyond doubt. But when investors begin to demand a clear return cycle, the “strongest model” label cannot directly answer the two questions of “when will it be profitable” and “how will it be profitable.”

According to QbitAI, OpenAI confidentially submitted its IPO prospectus in June this year, but the CFO’s public remarks indicate that the company is still considering a listing in 2027. This means the private market will need to continue providing funding for at least another year, while funding conditions are becoming harsher.

Prediction markets have already reacted: according to data cited by CryptoBriefing, the market prices the probability of “OpenAI’s IPO valuation falling below $1 trillion before January 2028” at 23.7%.

Frozen Window: Anthropic’s IPO Becomes an Industry Barometer

At present, the entire AI private-market ecosystem is effectively in a “waiting state”: the outcome of Anthropic’s IPO will become a key reference for judging the overall repricing range of the AI industry. If Anthropic’s share price remains stable after listing, institutional investor confidence will be restored, and funding windows for subsequent AI startups will still exist. If the IPO result falls short of expectations, chain reactions will spread from leading companies to mid-tier companies, and revenue multiples across the AI private market will face further compression.

This downward revision is occurring during a period of rapid AI capability development, not technological stagnation. OpenAI and Anthropic have released multiple model versions with substantive progress over the past 12 months, and their user bases continue to grow. The valuation adjustment does not come from a collapse on the technology side, but from the capital market repricing the question of whether technological leadership can be quickly converted into a commercial moat.

Independent Judgment

This round of valuation cuts is not the popping of an AI bubble, but a stratification of the AI narrative: the pure “capability race” logic can no longer support top-tier valuations on its own, and the market is beginning to demand a sustainable business model at the same time. OpenAI and Anthropic’s technological leadership remains intact, but their valuations will increasingly be anchored by commercial revenue growth, infrastructure cost control capability, and profitability timelines, rather than relying solely on model capability rankings.

For the entire AI ecosystem, this is in fact a healthy corrective signal. The valuation bubble accumulated during the funding frenzy of the past two years needs to be gradually digested through real commercial data. The real question is not whether the leading companies can survive—of course they can—but whether, after capital becomes more selective, mid-tier AI companies that have not yet established a clear commercial path still have enough time to find the answer.