As of Sep 22, 2026
All companies

AI researchFounded

Thinking Machines Lab

Builds customizable AI models and tools.

Mira Murati
Mira Murati
John Schulman
John Schulman
Barret Zoph
Barret Zoph

Business performance

Read the revenue model
Valuation
$12.00B
ARR
Not disclosed
Annual revenue
Not disclosed
Users / customers
Not disclosed
Net income
Not disclosed
Revenue multiple
Unavailable

Reading the numbers

Training and compute usage are Tinker’s commercial units. Model downloads measure research distribution; the seed financing is not revenue.

01What it sells and who buys it

Thinking Machines provides Tinker for adapting models to customer data and tasks, alongside open Inkling models. Its buyers include researchers and development teams customizing AI.

02How the business makes money

Tinker charges per million input, output and training tokens, plus monthly checkpoint storage per GB. Downloading open models and paying for managed training are distinct usage paths.

03Marketing and customer acquisition

After financing the research team, Thinking Machines linked open models to a managed training product.

  1. 01

    Target developers customizing models

    Tinker provides a training environment for task-specific models. Inkling offers evaluation through both downloadable models and managed experimentation.

    Source
  2. 02

    Financing the next stage

    A $2 billion seed round led by a16z in July 2025 valued the company at $12 billion. Initial financing established research and computing capacity, followed by the release of developer training products.

    Source
  3. 03

    How distribution and adoption expanded

    Open models are linked to Hugging Face downloads and direct customization through Tinker. Model cards, benchmarks and training documentation help developers evaluate the technology and run a first experiment. Managed training provides a commercial route from that research visibility.

    Source

How the growth mechanism works

  1. Read the research
  2. Test the open model
  3. Customize through Tinker
  4. Expand compute usage

Open models build technical credibility; managed training reduces execution work. Early financing backed the team and research capability and must be read separately from later paid adoption.

04Funding and expansion

A $2 billion seed round led by a16z in July 2025 valued the company at $12 billion. Initial financing established research and computing capacity, followed by the release of developer training products.

Further reading

  1. 01thinkingmachines.aiRead source
  2. 02wired.comRead source
  3. 03tinker-docs.thinkingmachines.aiRead source
  4. 04rothschildandco.comRead source
  5. 05research.contrary.comRead source
  6. 06techcrunch.comRead source
  7. 07joschu.netRead source
  8. 08barretzoph.github.ioRead source
  9. 09en.wikipedia.orgRead source
  10. 10joschu.netRead source