Thinking Machines AI Startup Pursues $1B Funding Round at $40 Billion Valuation With Accel, Nvidia

Thinking Machines Pursues Major Funding Round

Thinking Machines, the AI startup founded by former OpenAI CTO Mira Murati in early 2025, is negotiating a $1 billion funding round at a $40 billion valuation, according to reports from The Information1

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. Existing investor Accel is in discussions to lead the fundraise, while Nvidia is considering a substantial $2.5 billion investment that would represent roughly half of a potential $5 billion to $6 billion total round2

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. The AI lab has rapidly emerged as one of the industry's most closely watched newcomers since Murati's departure from OpenAI, where she played a pivotal role in developing ChatGPT.

Valuation Reflects Steep Revenue Multiple

The proposed $40 billion valuation represents a fourfold increase from the $10 billion pre-investment valuation Thinking Machines achieved in July 20253

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. However, this figure falls short of the over $50 billion valuation the company reportedly sought late last year1

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. With an annual revenue run rate standing at over $100 million, the $40 billion valuation reflects an extraordinarily high revenue multiple1

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. Some reports indicate the company is generating at least a few hundred million dollars in annualized revenue through its business model of selling tools to customize AI models using proprietary data3

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Nvidia Partnership Deepens Strategic Ties

Nvidia's potential participation would significantly expand the chip giant's role beyond its core hardware and computing infrastructure business. The funding talks build on an existing relationship established in March, when Thinking Machines and Nvidia announced a multiyear partnership2

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. The AI startup committed to deploying at least 1 gigawatt of Nvidia's next-generation Vera Rubin platform, engineered specifically for agentic AI factories and reasoning workloads2

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. This arrangement could strengthen future demand for Nvidia systems while providing Thinking Machines with the computing capacity required for AI training and inference at scale.

Revenue Model Centers on Customizable AI

Thinking Machines generates revenue through its distinctive approach to customizable AI models. In July, the company introduced Inkling, an open-weight AI model that generates income by charging usage-based compute fees for adapting models on proprietary data through its Tinker platform1

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. While the company's open-weight models are available for free, it monetizes by selling businesses tools to customize AI models using their own data3

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. The startup has positioned itself around systems and tools that allow organizations to adapt models to their specific needs and goals.

Record-Breaking Seed Round and Investor Confidence

The startup's previous fundraise—a $2 billion round in July 2025 that stands among the largest seed financings in Silicon Valley history—valued the company at $12 billion1

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. Andreessen Horowitz led that investment, joined by Nvidia, GV, Lightspeed, and Conviction Partners1

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. Investors backed the round largely on the pedigree of Mira Murati and the former OpenAI researchers who joined her at the AI lab. By November, the company was already discussing another round at a valuation as high as $60 billion, though those talks had not been finalized3

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Leadership Challenges and Strategic Direction

Despite rapid growth, Thinking Machines has experienced several high-profile departures, with some co-founders including Lilian Weng and Luke Metz returning to OpenAI1

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. The new capital, if secured, would be deployed to train models, rent computing infrastructure, and hire employees as the company scales its operations3

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. The fundraising talks underscore how investors continue placing multibillion-dollar bets on independent AI labs despite the steep costs of developing frontier models. Watch whether the company can maintain its momentum while addressing talent retention and achieving the ambitious valuations that reflect investor confidence in customizable AI systems as a critical gap in the current AI landscape.