Thinking Machines' bet: real-time, customizable AI — $2B seed, 1GW of Nvidia, then Inkling

Thinking Machines Lab is an AI research lab, founded by former OpenAI CTO Mira Murati, building multimodal frontier models that work collaboratively in real time and can be fine-tuned by users on its Tinker platform.

That frontier AI's next leap is real-time interaction and customization, not just scale — and that a record seed round plus 1GW of Nvidia compute could buy it.

$2B seed led by a16z in July 2025 at a $12B post-money valuation — the largest seed round on record — with Nvidia, AMD, Accel, ServiceNow, Cisco and Jane Street participating

Mira Murati left OpenAI in late 2024 after six years, including as CTO of ChatGPT, and founded Thinking Machines Lab in February 2025 with OpenAI co-founder John Schulman as chief scientist and Barret Zoph as CTO. The 29-person founding team was drawn mostly from OpenAI, Character AI and Google DeepMind. Its launch post said AI systems remain hard for people to customize, so the lab would build multimodal models that 'work with people collaboratively.'

In July 2025 the company closed a $2B seed led by a16z at a $12B post-money valuation — the largest seed round in history — with Nvidia, AMD, Accel, ServiceNow, Cisco and Jane Street participating, despite no revenue or products yet. It shipped its first product, the Tinker API, in October 2025. In March 2026 it signed a multi-year partnership with Nvidia to deploy at least one gigawatt of Vera Rubin systems from 2027, plus a strategic Nvidia investment; in May 2026 it previewed its first 'interaction model,' TML-Interaction-Small, which streams audio, video and text in 200-millisecond chunks instead of turn-taking. Along the way it lost four co-founders: one to Meta, three back to OpenAI.

In July 2026 it released Inkling, its first open-weights model — a 975B-parameter multimodal mixture-of-experts model under an Apache-2.0 licence — explicitly positioned not as the strongest model but as a base for customer fine-tuning on Tinker. The bet is still being tested: $2B+ raised, a >$12B valuation, a 1GW Nvidia supply deal, and first products shipped in 2025–2026.

Talent was the wedge: two-thirds of the founding team came from OpenAI, and investors bet on people before product — the $2B seed closed months before anything shipped.

The thesis was differentiation: instead of another chatbot, build models that are real-time, understandable and customizable — a direction the big labs weren't optimizing for.

Compute became the moat strategy: locking up 1GW of Vera Rubin plus a strategic Nvidia investment turned a seed-stage lab into a capital-infrastructure play.

The risk showed in the exits: four co-founders left within roughly 18 months, a reminder that a talent-concentrated lab's biggest asset is also its most liquid one.

A record round buys talent and compute, but the bet lands only if the product matches the thesis — and a talent-first lab can leak exactly what made it valuable when co-founders leave.

As of September 2026, Thinking Machines Lab remains private, with more than $2B raised and a valuation above $12B. It has shipped two product lines since late 2025: the Tinker fine-tuning API and the open-weights Inkling model (975B parameters, Apache-2.0, 45 trillion training tokens), positioned as a base for customization rather than a frontier model. In March 2026 it signed an Nvidia partnership to deploy at least one gigawatt of Vera Rubin systems from 2027, with Nvidia also investing. Its biggest unresolved risk is people: four co-founders left, one to Meta and three back to OpenAI.