Thinking Machines Lab, a startup founded by former OpenAI executive Mira Murati, is reportedly in talks to raise a new funding round that could value the company at around $50 billion. If finalised, the deal would push the year-old company into the top tier of global private startups, multiplying its valuation more than fourfold since July.
The new round is still being negotiated, with insiders suggesting the valuation could land anywhere between $50 billion and $60 billion, depending on investor appetite. This follows an extraordinary $2 billion seed round secured in July at a $12 billion valuation, one of the largest early-stage raises in tech history.
The upcoming financing will support several priorities:
- Expanding research teams across model development and safety
- Scaling compute and infrastructure to train next-generation systems
- Accelerating adoption of Tinker, the company’s early flagship product
- Developing new tools aimed at enhancing collaboration between people and intelligent systems
Thinking Machines already counts leading institutions such as Stanford and Princeton among early users of its technology, with paying business customers now integrating Tinker into their workflows.
A founding team built from OpenAI’s core
Thinking Machines is powered by a star-studded group of engineers and researchers drawn from OpenAI. Murati, who previously served as CTO and briefly interim CEO, left OpenAI in late 2024 after months of internal turbulence following Sam Altman’s ouster and eventual return.
She was soon joined by several high-profile colleagues, including:
- John Schulman, OpenAI co-founder and one of the architects behind reinforcement learning from human feedback
- Barret Zoph, former VP of research, known for advancing frontier model training
This concentration of expertise positions the company as one of the strongest new research labs to emerge since OpenAI’s early days.
Building tools for human–AI collaboration
Unveiled in February, Thinking Machines’ mission is to design advanced models and build tools that help people work more effectively with intelligent systems. Its first product, Tinker, enables companies and researchers to customise large models with far less friction than traditional fine-tuning workflows.
Early feedback from both academia and enterprise users has been strong, and the company is doubling down on expanding Tinker’s capabilities while preparing additional products aimed at making AI systems more adaptive and controllable.
As investors continue pouring capital into next-generation AI labs, Thinking Machines stands out for its ambition, speed and concentration of talent and its next funding round could redefine what early-stage scale looks like in this industry.
