Thinking Machines Nears $1B Raise at $40B Valuation, Below Prior Target

Thinking Machines is back in the market for capital, and the numbers tell an interesting story about where AI lab valuations sit right now.

The Information reported Thursday that the AI lab founded by former OpenAI CTO Mira Murati is in discussions to raise $1 billion at a valuation of at least $40 billion. Existing investor Accel is reportedly in talks to lead the round. Neither Accel nor Thinking Machines responded to requests for comment.

The figure matters for what it isn't. Late last year, Thinking Machines reportedly sought a $50 billion valuation. If this round closes at $40 billion, the company will have priced down roughly 20% from that target, even as its business has grown. That is not the trajectory venture investors typically want to see from a marquee AI name, and it deserves scrutiny.

The Revenue Math

Here is the number that should catch every investor's attention: Thinking Machines' annual revenue run rate stands at over $100 million, according to a source with knowledge of the company's financials. At a $40 billion valuation, that implies a revenue multiple north of 400 times. Even by the frothy standards of the current AI cycle, that is an extraordinarily high multiple.

Multiples like this are not unprecedented in AI. Investors have shown a willingness to pay up for labs perceived to be at the frontier of model development, treating revenue as a lagging indicator of technical talent and future optionality rather than a present-tense valuation anchor. Still, a 400x multiple assumes a lot of things go right, and it leaves very little room for error if growth slows or competition intensifies.

The company's product strategy gives some texture to that revenue figure. In July, Thinking Machines launched Inkling, an open-weight model, and the company generates income through usage-based compute fees on its Tinker platform, which lets customers adapt models using proprietary data. That is a real, monetizable product, not just a research lab burning cash on compute with no path to revenue. It is a meaningfully different model from pure research shops, and it gives Thinking Machines a business to point to beyond its founding team's pedigree.

Pedigree, though, was the entire pitch the first time around. Thinking Machines closed a $2 billion seed round, one of the largest seed financings on record, at a $12 billion valuation. Andreessen Horowitz led that round, with Nvidia, GV, Lightspeed, and Conviction Partners participating. Investors backed that deal almost entirely on the strength of Murati's reputation and the roster of former OpenAI researchers who followed her out the door.

That roster has thinned since. Several co-founders have left, including Lilian Weng and Luke Metz, both of whom returned to OpenAI. Barret Zoph, another co-founder, also departed and has since moved through Google after a stint elsewhere. For a company whose original valuation rested heavily on the strength of its founding team, high-profile departures back to a chief competitor are not a footnote. They are a data point that any investor evaluating this new round should weigh carefully.

Why It Matters

The jump from a $12 billion seed valuation to a potential $40 billion mark in roughly a year and a half is still substantial, more than 3x. Investors clearly believe the Tinker platform and Inkling's usage-based revenue model represent real commercial traction, not just a research narrative. That is a meaningful shift from a company that raised its first big round almost entirely on founder credibility.

But the gap between the $50 billion figure reportedly sought last year and the $40 billion figure now on the table is the detail that separates this story from a straightforward up-round narrative. Something changed investor sentiment over the past several months, whether that is the co-founder exits, broader repricing of AI lab valuations across the sector, or simply a more disciplined bar being applied by lead investors like Accel. Probably some combination of all three.

Accel's willingness to lead at this level is itself informative. The firm is already a backer, so its participation signals conviction rather than a fresh bet, but leading a $1 billion round at $40 billion is a significant commitment even for existing shareholders. It suggests Accel sees enough in the Tinker revenue trajectory and the broader AI infrastructure opportunity to double down, even amid the valuation reset and the leadership churn.

The revenue multiple, meanwhile, remains the number to watch closely. A 400x multiple only makes sense if the market believes Thinking Machines is on a path toward revenue growth that dwarfs its current run rate within a few years. That is a common bet in AI right now, but it is a bet, not a certainty, and the sector has already seen valuations compress quickly when growth assumptions fail to hold.

What Investors Should Watch

Three things will determine whether this round proves to be smart capital or an expensive lesson. First, whether Thinking Machines can grow its $100 million run rate fast enough to justify the multiple, meaning several multiples of growth over the next 12 to 18 months rather than incremental gains. Second, whether the co-founder departures stabilize or continue, since further high-profile exits to OpenAI or elsewhere would undercut the talent-pedigree thesis that underpinned the original seed valuation. Third, whether Tinker's usage-based compute fee model scales the way subscription and infrastructure businesses typically do, with expanding margins and sticky customers, or whether it proves more cyclical and price-sensitive than investors currently assume.

None of these questions have clear answers yet. The round has not closed, and the $40 billion figure could still shift before ink hits paper. What is clear is that Thinking Machines' second major fundraise will be judged on business fundamentals in a way its first one never had to be.