AI startup Thinking Machines clinches capital and a major chip supply deal from Nvidia

AI startup Thinking Machines Lab said on Tuesday it has struck a multi-year partnership with Nvidia that will see it receive a significant investment and procure at least one gigawatt of the chipmaker's next-generation processors.

Financial terms of the deal were not disclosed.

Under the agreement, Thinking Machines - founded last year by former OpenAI ‌Chief Technology ⁠Officer ⁠Mira Murati - will deploy Nvidia's upcoming Vera Rubin systems starting early next year. The computing power will primarily be used to train the startup's artificial intelligence models.


Industry executives have said ​1 gigawatt of computing power, enough to power roughly 750,000 U.S. homes, can cost around $50 billion.

The deal will help Thinking Machines compete with larger rivals ​in building powerful AI systems, and underscores ⁠the industry's eagerness ‌to scale computing capacity.

Thinking Machines quickly became one ​of Silicon ​Valley's most closely watched AI startups after raising about $2 billion in ⁠a seed funding round led by Andreessen Horowitz ​that valued the company at $12 billion. Nvidia was also an ​investor in the round.

The startup has recently been seeking to raise more in a new funding round that could value it at tens of billions of dollars, sources told Reuters earlier.

The company has recently seen several departures, including co-founder and former Chief Technology Officer Barret Zoph and co-founder ‌Luke Metz, who both returned to their former employer OpenAI amid fierce competition for AI talent.

The partnership also highlights ​Nvidia's growing ​role as a financier ⁠of the startups that rely on its AI chips.

It has made a recent $30 billion investment in OpenAI and invested $10 billion in Anthropic, while also supplying ​the graphics processing units (GPUs) used to train and run their models, a dynamic that some industry analysts say creates a circular flow of capital and computing resources. That in turn has given rise to comparisons with the late 1990s tech bubble.