Accel reportedly in talks to lead $1B round for Thinking Machines at $40B valuation
- ID
- 21175
- Status
- summarized
- Published
- 04 Sep 2026, 3:36 AM
- Fetched
- 04 Sep 2026, 5:09 AM
- Provider
- TechCrunch
- Category
- technology
- Original URL
- https://techcrunch.com/2026/09/03/accel-reportedly-in-talks-to-lead-1b-round-for-thinking-machines-at-40b-valuation/
- Source URL
- https://techcrunch.com/feed/
Summary
- Score
- 4.5
- Created
- 04 Sep 2026, 5:10 AM
- Tags
- Audience
- ai_ml_learnerssaas_startup_founders
What happened
Accel is in talks to lead a $1B round for Thinking Machines Lab, the AI startup founded by former OpenAI CTO Mira Murati, at a $40B valuation—down from the $50B it reportedly sought last year. The company has over $100M in annual revenue run rate (a ~400x multiple), earns via usage-based compute fees on its Tinker platform for adapting its open-weight Inkling model on proprietary data, and has seen co-founders Lilian Weng and Luke Metz depart back to OpenAI.
Why it matters
The revenue model is the concrete signal here: Thinking Machines is monetizing open-weight models not through licensing but through usage-based compute on a fine-tuning platform (Tinker). If you build with or around open-weight models, this validates a platform-play business model worth comparing against your own. The 400x revenue multiple also tells you VC money is still pricing AI labs on team pedigree and narrative, not fundamentals—useful context if you're raising or evaluating AI startup offers.
Discussion angle
Is the open-weight model + fine-tuning platform (Tinker/Inkling) a durable revenue model, or does it collapse once hyperscalers bundle the same thing for cheaper? Compare against what local builders would actually pay for.