Thinking Machines Lab, the AI startup founded by former OpenAI chief technology officer Mira Murati, is reportedly raising $5 billion in a round led by venture firm Accel at a $40 billion pre-money valuation. The deal, which could close as soon as this week, would more than triple the company's valuation since its last publicly reported round. It arrives amid a week of extraordinary AI capital flows, including a $1.3 billion raise for inference startup Fal and a flurry of enterprise and robotics deals. But the sheer scale of Thinking Machines' ask, for a company that has shipped relatively little public product, stands out even in a market numbed by nine- and ten-figure checks.
The round underscores a growing tension in the AI industry between valuations built on founder pedigree and technical promise versus those backed by demonstrated revenue and shipped products. Murati departed OpenAI in September 2024 and launched Thinking Machines Lab with a team of former OpenAI, Google, and Meta researchers, positioning the company as a builder of more collaborative, customizable AI systems. A $40 billion valuation would place the roughly two-year-old startup in rarefied company, ahead of many firms with years of enterprise traction, and it comes as investors increasingly bet on the people and infrastructure believed capable of defining AI's next phase rather than on current product footprints alone.
A Tripling in Valuation
According to reports, Accel is leading the new $5 billion financing round for Thinking Machines Lab at a $40 billion pre-money valuation, a figure that would more than triple the company's valuation from its previous publicly disclosed funding. The deal could close within the week, according to people familiar with the discussions, though neither Thinking Machines nor Accel has formally confirmed the terms. If finalized, the round would rank among the largest private AI financings of 2026, rivaling infrastructure-heavy deals like Fal's $1.3 billion raise and Anthropic's reported infrastructure commitments.
The scale of the valuation jump has drawn scrutiny from investors who note that Thinking Machines has disclosed relatively little about its product roadmap or commercial traction compared to peers like OpenAI, Anthropic, or Prime Intellect, which reported roughly $100 million in annual recurring revenue alongside its own funding round this week. Instead, the company's value proposition has rested heavily on Murati's track record as OpenAI's former CTO and the caliber of researchers she has recruited since founding the company. That dynamic has become increasingly common in frontier AI investing, where capital often precedes product by a wide margin.
Why Investors Are Betting on Pedigree
Thinking Machines Lab has positioned itself around building AI systems that are more adaptable and collaborative than existing chatbots and assistants, aiming to let businesses and individuals customize models to their own workflows rather than relying on one-size-fits-all products from OpenAI or Google. Murati has assembled a team that includes several high-profile departures from OpenAI's research and engineering divisions, alongside veterans of Google DeepMind and Meta's AI labs. That talent concentration, rather than any single shipped product, appears to be driving much of the valuation.
The bet mirrors a broader pattern this week in AI funding, where investors rewarded both infrastructure plays and founder-driven research labs with outsized valuations. Fal, the AI inference startup serving image, video, and audio generation workloads, doubled its valuation to $16 billion on a $1.3 billion raise, while Positron, an AI-inference-chip startup, was reportedly in talks for financing that could value it at up to $5 billion. Against that backdrop, a $40 billion figure for Thinking Machines reflects investor appetite for exposure to frontier AI research even without the enterprise contracts or usage metrics that typically justify such valuations.
A Crowded and Expensive Funding Market
The Thinking Machines round lands in the middle of one of the busiest weeks for AI dealmaking this year. Prime Intellect raised $130 million at a $1 billion valuation for its enterprise AI-agent tools. Ollama, the platform for running AI models locally, closed a $65 million Series B after doubling its developer base to 8.9 million since January. Twelve Labs raised $100 million for video-AI technology alongside a strategic deal with Amazon Web Services, and robotics startup Tutor Intelligence secured $75 million from Andreessen Horowitz.
Each of these deals reflects a different corner of the AI stack, from inference and local deployment to vertical enterprise software and physical robotics. But the Thinking Machines figure dwarfs them all, raising questions about how venture investors are pricing risk in a market where capital is abundant and competition for access to top AI talent is fierce. Some investors argue that backing proven teams early, even at steep valuations, remains cheaper than trying to catch up later once a company has established a technical lead, a logic that has repeatedly played out with OpenAI, Anthropic, and now potentially Thinking Machines.
Investors are no longer just underwriting products, they're underwriting entire research agendas and the teams capable of executing them. That's a very different kind of bet than venture capital used to make.
What Happens Next
If the round closes as reported, Thinking Machines Lab will face mounting pressure to translate its valuation into visible products and revenue, particularly as OpenAI President Greg Brockman has signaled the company's own path toward a possible 2027 initial public offering following what he described as a revenue inflection driven by enterprise adoption. Investors who pay premium prices for research-stage companies typically expect a clearer commercial roadmap within 12 to 18 months, and Thinking Machines will likely need to demonstrate differentiated capabilities against incumbents that already have massive distribution, including OpenAI's ChatGPT ecosystem and Google's Gemini models.
The deal also illustrates how founder reputation has become its own asset class in AI investing, with venture firms willing to commit billions based on team composition and research direction rather than traditional financial metrics. Whether that bet pays off will depend heavily on what Thinking Machines ultimately ships, and how it differentiates itself in a market that already includes dominant players backed by hundreds of billions of dollars in infrastructure commitments. For now, the reported $40 billion valuation cements Murati's standing as one of the most closely watched founders in the industry, barely two years after her departure from OpenAI.
Sources
- https://www.nbcnews.com/artificial-intelligence
- https://www.sciencedaily.com/news/computers_math/artificial_intelligence/
- https://aibriefing.dev/stories
- https://www.wsj.com/tech/ai
- https://teknoozet.online/en/category/ai
- https://www.moneycontrol.com/artificial-intelligence/
- https://www.newsnow.co.uk/h/AI
- https://techcrunch.com/category/artificial-intelligence/
- https://aiweekly.co/
- https://www.prnewswire.com/news-releases/latest-news-topics/artificial-intelligence/
- https://www.siliconreport.com/ai-startup-news
- https://www.businesswire.com/newsroom/industry/technology/artificial-intelligence
- https://daily.rclabs.in/t/business
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