Accel Eyes $1B Bet on Mira Murati's Thinking Machines at $40B Valuation

TL;DR

• Accel is reportedly in talks to lead a massive $1 billion funding round for Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, at a $40 billion valuation.
• The startup, which only emerged from stealth in early 2025, is already generating over $100 million in annualized revenue run rate, a key driver behind its staggering valuation jump from $10 billion just months ago.
• If completed, the deal would mark one of the largest early-stage bets in AI history and underscores the continued frenzy among top VCs to back frontier AI labs led by proven founders.

A Powerhouse Deal in the Making

Accel is closing in on what could be one of the most aggressive venture bets of the year. According to reports circulating this week, the storied Silicon Valley firm is in advanced talks to lead a $1 billion investment in Thinking Machines Lab at a $40 billion valuation.

The talks are still ongoing and terms have not been finalized, but the sheer scale of the proposed round has sent shockwaves through Silicon Valley. If completed at those terms, it would quadruple the valuation Thinking Machines commanded just months ago and instantly place the year-old lab among the most valuable private AI companies in the world, alongside OpenAI, Anthropic, and Elon Musk's xAI.

Accel, known for early bets on Facebook, Slack, and Spotify, has been notably selective in the generative AI wave compared to rivals like Andreessen Horowitz and Sequoia. Leading a round of this magnitude would signal a decisive, high-conviction move to secure a foothold in the frontier model race.

From Stealth to $100 Million Run Rate

Thinking Machines Lab was founded by Mira Murati after her high-profile departure as Chief Technology Officer of OpenAI in September 2024. Murati, who oversaw the development of ChatGPT, DALL-E, and GPT-4, launched the lab in February 2025 with a core team of ex-OpenAI, Meta, and Mistral researchers.

The company's mission has been deliberately broad: to build multimodal frontier AI systems that are more customizable, collaborative, and widely accessible than closed competitors. While it has yet to release a flagship public model, the startup's enterprise-focused approach appears to be paying off commercially.

Sources close to the company indicate Thinking Machines has already crossed a $100 million annual revenue run rate, driven by early partnerships, API access, and custom model deployments for enterprise clients. For a research lab that has been operating publicly for less than a year, that level of monetization is exceptionally rare and helps explain why investors are willing to pay a premium.

The startup previously raised a $2 billion seed round earlier this year at a reported $10 billion valuation, at the time one of the largest seed rounds on record. The proposed new valuation would represent a 4x markup in under six months.

What Justifies a $40 Billion Price Tag?

On paper, a $40 billion valuation for a company without a widely released product seems astronomical. But in the current AI funding climate, the valuation reflects three powerful forces: team, traction, and timing.

First is founder pedigree. Murati is one of the most recognized technical leaders to emerge from OpenAI, and her co-founding team includes veterans like former OpenAI researcher John Schulman and other key architects behind ChatGPT. For investors who missed out on OpenAI and Anthropic, Thinking Machines represents a rare second chance to back a proven frontier team at an early stage.

Second is the revenue signal. Unlike many frontier labs that burn hundreds of millions on compute before generating a dollar of revenue, Thinking Machines' reported $100 million run rate suggests product-market fit and a viable enterprise go-to-market engine. Investors are no longer just valuing research potential; they are valuing a business that can sell.

Finally, there is the underlying technology thesis. Thinking Machines is reportedly focused on building more efficient, agentic, and collaborative AI systems that can be deeply customized by businesses, rather than one-size-fits-all foundation models. In a market increasingly concerned with AI moats and defensibility, that vision of controllable, enterprise-grade superintelligence is highly attractive.

What This Means for the AI Funding Landscape

The potential Accel-Thinking Machines deal is the latest sign that the AI funding frenzy is not cooling down — it is accelerating and concentrating at the top.

Despite talk of an AI bubble and investor fatigue, capital continues to flood into a small handful of elite labs perceived as having a legitimate shot at artificial general intelligence. In 2025 alone, frontier labs raised tens of billions, with valuations routinely defying traditional SaaS multiples. A $40 billion valuation for Thinking Machines would cement the idea that investors are pricing these companies not as software startups, but as potential platform owners for the next era of computing.

It also highlights a growing valuation gap in AI. While hundreds of application-layer AI startups struggle to raise Series A rounds, infrastructure and model-layer companies led by marquee founders are commanding unprecedented premiums. For VCs, the fear of missing out on the next OpenAI far outweighs the risk of overpaying early.

If Accel succeeds in leading this round, expect a domino effect. Other major firms will be pressured to make similarly outsized bets to stay relevant in AI, and the bar for what constitutes a “large” AI funding round will be reset yet again. For now, all eyes are on whether Murati and Accel can close a deal that could define the next chapter of the AI boom.

AndroGuider Team

Articles written by the AndroGuider team. We try to make them thorough and informational while being easy to read.