Nvidia makes significant investment in Thinking Machines Lab, will supply 1 gigawatt of AI chips

Reviewed byNidhi Govil

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Nvidia has struck a multiyear strategic partnership with Mira Murati's Thinking Machines Lab, combining a significant investment with a chip supply deal worth potentially $50 billion. The AI research lab will deploy at least 1 gigawatt of Nvidia's next-generation Vera Rubin systems starting in 2027, enough computing power to run 750,000 homes. The deal highlights both the AI industry's hunger for compute capacity and Nvidia's growing role as a financier of its own customers.

Nvidia Inks Major Strategic Partnership with Thinking Machines Lab

Nvidia has announced a multiyear strategic partnership with Thinking Machines Lab, the AI research lab founded by former OpenAI Chief Technology Officer Mira Murati

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. The deal combines a significant investment in the artificial intelligence startup with a massive chip supply deal that will see Thinking Machines deploy at least 1 gigawatt of Nvidia's forthcoming Vera Rubin systems starting early next year

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. While financial terms were not disclosed, industry executives estimate that 1 gigawatt of computing power—enough to power roughly 750,000 U.S. homes—can cost around $50 billion

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Source: NVIDIA

Source: NVIDIA

Massive Computing Power to Fuel AI Models Development

The computing power provided through this partnership will primarily support frontier model training and platforms delivering customizable AI at scale

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. The agreement also includes a commitment to develop training and serving systems specifically designed for Nvidia architecture, while aiming to broaden access to frontier AI and open models for enterprises, research institutions, and the scientific community

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. "Nvidia's technology is the foundation on which the entire field is built," Murati said in a statement. "This partnership accelerates our capacity to build AI that people can shape and make their own, as it shapes human potential in turn"

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Source: ET

Source: ET

Thinking Machines Lab's Rapid Rise and Recent Challenges

Thinking Machines Lab has quickly become one of Silicon Valley's most closely watched startups since raising approximately $2 billion in a seed funding round led by Andreessen Horowitz that valued the company at $12 billion

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. Nvidia was also an investor in that round, along with Accel and even rival chipmaker AMD's venture arm

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. The startup has been seeking to raise more funding in a new round that could value it at $50 billion, quadrupling its valuation from July

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. However, the company has faced several high-profile departures, including co-founder and former CTO Barret Zoph and co-founder Luke Metz, who both returned to OpenAI amid fierce competition for AI talent

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Nvidia's Growing Role as AI Industry Financier

This deal underscores Nvidia's expanding position not just as a chip supplier but as a major financier of the AI chips ecosystem

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. The semiconductor giant has recently made a $30 billion investment in OpenAI and invested $10 billion in Anthropic, while also supplying the graphics processing units used to train and run their models

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. This dynamic creates a circular flow of capital and computing resources that some industry analysts compare to the late 1990s tech bubble

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. "Thinking Machines has brought together a world-class team to advance the frontier of AI," said Jensen Huang, Nvidia's CEO. "We are thrilled to partner with Thinking Machines to realize their exciting vision for the future of AI"

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Source: Market Screener

Source: Market Screener

The AI Infrastructure Arms Race Intensifies

This agreement arrives as AI companies remain hungry for any compute capacity they can secure. Jensen Huang has predicted that companies could spend $3 trillion to $4 trillion on AI infrastructure by the end of the decade

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. The scale of these deals continues to grow, with rival OpenAI allegedly inking a historic $300 billion compute deal with Oracle in 2025

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. For Thinking Machines Lab, this partnership provides the infrastructure foundation needed to compete with larger rivals in building powerful AI systems that are understandable, customizable, and collaborative

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. As the race to build more capable AI models accelerates, access to cutting-edge computing power from Nvidia's Vera Rubin platform may prove decisive in determining which startups can deliver on their ambitious visions for shaping the future of artificial intelligence.

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