On October 26, Anthropic filed a Form S-1 with the SEC, laying out its business, finances and risks ahead of the IPO. The company plans to list on Nasdaq under the ticker ANT, tentatively in November 2026. No official date has been set, but the WSJ and Reuters point to the week of November 16.
The filing shows $16.3B in revenue for the first half (up roughly 1,300% year over year) and a net loss of $80.7B, most of it a non-cash revaluation of liabilities. It also includes a detailed list of risks, among them scenarios in which advanced AI could cause “catastrophic or existential” harm. Seven founders keep 50.1% of the voting power through a special Class F share.
Until now, money has flowed into Anthropic and its competitors through private funding rounds, and valuations rose alongside the narrative. Now the market can compare revenue, token costs and the real cost of compute side by side.
The S-1 doesn’t state a valuation, but according to Reuters, investors are now eyeing $1.5T. A trillion-dollar valuation and a trillion-dollar business aren’t the same thing: paper value doesn’t guarantee that buying the shares will deliver comparable returns.
Then there’s the paradox of control. The company is raising public capital, yet the founders keep the final say: all public Class A shares combined will never hold more than 49.9% of the votes. In effect, investors are buying a seat on a ship whose course they have no power to influence. The setup isn’t unique, and the market has accepted it before. But in AI, where bets on long-term direction carry especially high stakes, who gets to decide becomes the central question.
Anthropic’s listing could hurt the AI market. According to the WSJ, the offering could raise $100B or more. The money will most likely concentrate in a few leaders, and smaller developers of models and infrastructure will find it even harder to secure funding. Competition may narrow not because of technology, but because of access to capital.
The S-1 isn’t an invitation to buy shares in the IPO. It’s the first transparent look at the economics of the most powerful AI models. Instead of fixating on headlines about trillions, it’s worth looking at how revenue growth, token costs and the ability to generate free cash flow stack up in the filing. That will show whether the boom is turning into a sustainable business or remains a story about valuation and expectations.
