On Wednesday Anthropic told investors gathered in San Francisco that it had taken $16.8 billion in revenue in the third quarter, up 45% on the quarter before, and that on an adjusted basis it was now profitable and generating cash. By Thursday Reuters was reporting that some of those same investors were discussing a stock market valuation nearer $1.5 trillion than the $2 trillion that had been circulating. CoreWeave's shares and bonds were falling, and the general reading had settled into a single word: slowdown. Growth of more than 100% in the second quarter had become 45% in the third, and that was enough to unsettle a market that had priced the company, and much of the infrastructure around it, on the earlier unprecedented pace.
The slowdown reading is fair, but other key figures received far less attention. Anthropic reportedly generated $1.70 of revenue for every dollar it spent on compute, which puts compute at roughly 59% of sales. Bloomberg's Ed Ludlow reported an 85% gross margin, meaning the cost of actually serving customers was around 15% of revenue. The gap between those two numbers, about 44% of everything Anthropic earned, is compute consumed by research and training, and it amounts to roughly three quarters of all the computing the company bought. Josh You at Epoch AI reached a similar estimate, putting 70 to 75% of Anthropic's compute into research. Anthropic's profit, in other words, is a decision about how much of its capacity to point at the next model rather than at paying customers, and its growth rate is partly a consequence of that decision. A company devoting three quarters of its compute to research, in a year when rents for Nvidia's Blackwell chips have risen by more than a quarter, was not necessarily short of demand. It may have been short of chips to train models and serve customers at the same time. (Anthropic also told investors that distillation, rival labs paying to train their own models on Claude's answers, had made up 5 to 7% of its revenue, and that it cut this back materially in the third quarter.)
Growth may still be held back by capacity and by the race to train the next model, and 45% a quarter would count as strong in almost any industry. The concern lies in how that growth is financed. A financial stability report from the IMF, published the day before the investor meeting, examined 14 disclosed AI deals since 2023 and found a common three-part structure. The large cloud companies put equity into financially weaker AI firms, around $300 billion in total, and because that equity is revalued every time the AI firm raises money at a higher price, the gains flow straight into the investor's reported profit. Lenders then supply debt, around $650 billion, some of it to the AI firms directly and some guaranteed or arranged by the investors, to be repaid from the AI firm's future revenue. In return the AI firms commit to spend on the investors' clouds and chips, about $1.4 trillion of it, which the cloud companies book as contracted future revenue and which the lenders behind the data centres treat as security.
How the IMF draws the loop: $300 billion of equity in (blue), $1.4 trillion of revenue commitments back (green), $650 billion of debt alongside (red), across 14 firms. Anthropic's $518 billion of cloud commitments is the largest single example of the green arcs. Source: IMF Global Financial Stability Report, October 2026.
Anthropic is the clearest case. Amazon and Google own stakes in it; Amazon's second quarter net income included $53.4 billion of non-operating gains, mostly from that holding, and Alphabet's included $99 billion from equity securities, partly from the same holding. Anthropic has in turn promised to spend at least $518 billion over a decade, much of it on their clouds. All three parts rest on one assumption, that Anthropic's revenue keeps growing fast enough to justify the valuation, service the debt and honour the spending. The IMF calls this wrong-way risk, because if the AI firm stumbles the equity falls, the debt sours and the promised revenue fails to arrive, all at once. This week showed a milder version in which the three parts moved separately. The valuation expectation dropped by $500 billion, the paper gains at Amazon and Alphabet shrank with it, and the $518 billion of commitments stayed exactly where they were.
Further down the chain the exposure spreads. Morgan Stanley figures cited by the Bank of England put AI-related debt issued by early September at around $450 billion, more than double the whole of last year, and the Bank found cloud companies accounting for 47% of sterling corporate bond issuance in 2026. Below the bonds sit neoclouds such as CoreWeave and Nebius and power suppliers such as Bloom Energy, which borrow against contracts tied to AI demand, and below them sit the funds. Value Aligned Research Advisors, a small firm in Princeton, New Jersey, had grown to $26.4 billion by June with Alphabet, Amazon, Nvidia and Bloom Energy among its largest holdings, then saw its flagship fund lose 44% in July when crowded AI positions unwound. On Thursday it was denying an unconfirmed rumour that it was in trouble. The same expectation of Anthropic's growth is being financed three times over, by bondholders, by hyperscalers marking up their stakes, and by leveraged investors, and strong results from the lab reassure all three and encourage them to extend further. A profitable Anthropic concentrates the risk rather than relieving it.
Whether the infrastructure can survive a stumble at the lab was the question put to Paul Kedrosky and Azeem Azhar on Ezra Klein's podcast this week. Kedrosky argues that large buildouts tend to end in overcapacity because cheap capital keeps them going past the point of demand, and that this time the whole structure depends on the private-market valuations of the labs. Azhar replies that the data centres get used whoever wins: if enterprises shift to cheaper open-weight models, Anthropic's margins suffer but the capital expenditure is still monetised.
“Everything is levered off the valuation of these companies that are currently sitting in private markets.”
Takeaways: Anthropic has answered the question of whether customers will pay for frontier AI, and left open the question of whether that payment can grow fast enough to support AI's financing stack. The upcoming IPO prospectus will be the first public audited look at a company critical to the future of AI economics.