A year ago, Thinking Machines was a seed-stage startup with a famous founder and no product to speak of. Now it is raising money at a valuation among the most richly priced in private AI. The company, founded by former OpenAI chief technology officer Mira Murati, is in talks to raise more than $1 billion at a pre-money valuation of at least $40 billion, according to people familiar with the matter, with Accel leading the round.
Nvidia is discussing contributing about $2.5 billion to the financing, the people said. If it joins, the investment would extend a pattern that has defined the AI capital markets this year: the chip maker writing large checks into the very labs whose computing needs its products serve. Nvidia and Thinking Machines already have a relationship; in March the two companies announced a strategic partnership around gigawatt-scale computing capacity, alongside an investment whose size was never disclosed but which Nvidia described at the time as substantial.
The numbers behind the round are what make it striking. Thinking Machines’ annualized revenue has only recently crossed $100 million, according to a person familiar with the company’s finances. A pre-money valuation of $40 billion against revenue of roughly $100 million implies a multiple that would have seemed impossible for a company of its maturity even in the frothiest moments of the AI boom. The valuation has traveled from the $12 billion attached to last year’s seed financing to $40 billion in roughly twelve months, a climb that has little to do with the company’s financial results and everything to do with the market’s appetite for AI talent and ambition.
The story of Thinking Machines is, at its core, a story about people. Ms. Murati left OpenAI in 2024 after a tenure that included leading the development of ChatGPT, and she took with her a reputation as one of the few executives in the industry who had shipped frontier products at scale. The company she built recruited heavily from OpenAI and other leading labs, and investors have treated the team as the asset, the same logic that drove enormous valuations for other founder-led AI startups before a single commercial product established itself.
What Thinking Machines actually does remains deliberately understated. The company describes its mission in terms of building artificial general intelligence, the long-hyped goal of machines that match or exceed human capability across a wide range of tasks, and it has said little about specific products. Its annualized revenue of just over $100 million suggests it has begun selling something, most likely research partnerships and early access to models, but the scale of the business is nowhere near the scale of its valuation.
That gap is the subject of an argument now dividing the AI investment community. One camp says the valuations are rational because the industry is early and the eventual winners will be worth trillions; under that logic, paying $40 billion for a position in a likely winner is cheap. The other camp says the market has priced in outcomes that may never arrive, and that companies with modest revenue and no clear moat are being valued on narrative rather than economics. Thinking Machines is a test case for both positions.
The involvement of Nvidia, if it closes, complicates the picture in an interesting way. Nvidia’s checks into AI labs have become a fixture of the funding market, and the company has said the investments are strategic rather than purely financial: by backing the labs that need the most compute, it locks in demand for its own products. For Thinking Machines, a $2.5 billion check from Nvidia would bring not just capital but access to the most sought-after hardware in the industry, a form of support that no other investor can offer.
Accel’s role as lead investor gives the round a familiar anchor. The venture firm backed the company from its earliest days. For Accel, the round is a chance to double down on a company whose valuation has quadrupled in a year, and to defend its position against newer investors willing to pay the current price. The syndicate, if it comes together, will include some of the largest names in technology investing, people familiar with the matter said.
The financing also says something about the state of the market for AI talent. Labs founded by famous researchers have become vehicles for enormous pools of capital, and the pattern repeats across the industry: a founder with a track record, a mission statement about AGI, and a valuation that grows faster than the business. Whether that pattern ends in consolidation, in enormous public companies or in write-downs is the question every investor in the space is effectively betting on.
Ms. Murati has said little publicly about the round, and the terms remain in flux; people familiar with the matter cautioned that negotiations could still change the valuation or the investor lineup. What is already clear is the direction of travel. A company that did not exist three years ago is now seeking capital at a valuation above that of many of the world’s most established technology firms, and the check it is asking Nvidia to write would be one of the largest single investments the chip maker has made in any startup.
For the AI industry, the round will be read as a signal about where the money is going. Compute-intensive frontier research is expensive, and the labs pursuing it need capital measured in the billions, not the millions. Thinking Machines’ investors are betting that Ms. Murati’s team can convert its reputation and its early revenue into a company that justifies the price. The round, if it closes, will make that bet one of the most visible in the industry, and its outcome will be measured against the only number that matters in the end: whether the valuation was a prediction or a mistake.
