Thinking Machines Lab Nears $5 Billion Raise Led by Accel at $40 Billion Valuation
Fundraising

Thinking Machines Lab Nears $5 Billion Raise Led by Accel at $40 Billion Valuation

Thinking Machines Lab, the artificial intelligence startup founded by former OpenAI chief technology officer Mira Murati, is reportedly on the verge of closing a major new funding round that could be finalized as early as this week.

According to a report by Business Insider, citing multiple people familiar with the deal, the company is raising $5 billion at a pre-money valuation of $40 billion. Venture firm Accel is said to be leading the round.

If completed, the deal would more than triple the valuation from the company's last public round and reinforce how much capital investors remain willing to commit to frontier AI labs.

A Steep Climb From a Record Seed Round

Thinking Machines Lab drew wide attention last year when it raised a $2 billion seed round before it had shipped a single product. That financing valued the company at more than $10 billion.

The new round would put the startup at roughly four times that earlier figure on a pre-money basis. Neither the company nor Accel offered comment: a Thinking Machines representative declined, and Accel did not reply to a request.

An Earlier Push at a Higher Price Fell Through

The current raise follows an unsuccessful attempt to secure funding at an even loftier price. Last year, the company sought a round at a $50 billion valuation, but those discussions were eventually dropped.

Signs of renewed fundraising surfaced in September, when The Information reported that Thinking Machines was in talks for fresh capital. The $40 billion pre-money figure now being discussed sits below that earlier target but still represents a substantial premium over the seed valuation.

OpenAI Roots and a Fine-Tuning Product

Much of the investor interest stems from the team's pedigree. Murati served as OpenAI's chief technology officer, and other key members of the startup worked on training early versions of ChatGPT.

The company's first product, Tinker, is designed to make it easier for users to fine-tune large language models for their own purposes. Fine-tuning lets developers adapt a general-purpose model to specific tasks without building one from scratch.

On Thursday, Thinking Machines released an updated version of Tinker, saying the new model has improved at AI coding tasks, an area where demand from developers and enterprises has grown quickly.

Talent Gains and Notable Departures

The startup has been able to recruit high-profile engineers, including competitive programmer Neal Wu. But it has also felt the effects of an intensifying fight for AI researchers across the industry.

Several founding members, including Barret Zoph, Luke Metz and Andrew Tulloch, have left for rival companies. Business Insider reported in May that roughly a third of the founding team had departed, citing factors that included very large compensation offers from competitors such as Meta and OpenAI.

That turnover makes the size of the new round notable. Investors appear to be betting on the company's technology and remaining leadership even as some of the people who helped launch it have moved on.

Investor Appetite for AI Labs Remains Strong

The reported deal adds to a pattern of outsized checks flowing into a small group of AI model developers. These companies require enormous sums to pay for computing power and to compete for scarce research talent.

For venture firms like Accel, leading a round of this scale signals confidence that a lab with a credible product and a strong technical bench can still carve out a position alongside larger, more established players.

What the Round Signals for Founders and the AI Market

For founders, the deal shows that reputation and team background continue to command extraordinary valuations in AI, even before a company has proven long-term revenue. It also shows that pricing is not unlimited, given the abandoned $50 billion effort.

For the broader industry, the combination of heavy funding and persistent talent churn highlights the central tension facing AI labs: capital is available, but keeping the people who build the technology is becoming just as important as raising money.

Source: Business Insider

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JeffkomStory Team

Editorial, JeffKom Story

The JeffKom Story newsroom covers startups, founders, funding and the technology shaping what’s next.

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