Mira Murati's Thinking Machines debuts first AI model
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Mira Murati's Thinking Machines on Wednesday released Inkling, its first AI model, betting enterprises want AI they can customize rather than simply rent from a handful of frontier labs.
Why it matters: Thinking Machines is making a different bet than many AI labs: that enterprises ultimately care less about the smartest general-purpose model than one they can make their own.
State of play: Inkling is the first foundational model release from Thinking Machines.
- The company is clear that Inkling is not the strongest model available, instead focusing on how the model is customizable, which could help users get better performance with lower costs.
- Instead of starting with another company's AI and modifying from there, this model was built from scratch and trained from the ground up.
- Thinking Machines trained the model on Nvidia's latest AI infrastructure, underscoring the company's partnership with the chip giant.
The intrigue: Thinking Machines used data generated by existing open models — including Kimi K2.5 from Chinese lab Moonshot AI — in its final training phase.
Between the lines: Instead of trying to beat competitors like OpenAI and Anthropic on model benchmarks, Thinking Machines is currently focused on customization.
- Still, Inkling could be the company's first step towards more powerful successors that Thinking Machines is already training.
- Thinking Machines is also previewing Inkling-Small, a lighter-weight model with weights that will be released after testing.
Zoom in: The full weights are available on Hugging Face and the model is now live for fine-tuning on Tinker, the company's customization platform.
Zoom out: Demand for open-weight models is growing as companies look for cheaper AI they can customize for their own applications.
- Organizations can fine tune open-weight models on their own proprietary data and deploy those models on infrastructure that they control, giving users more flexibility over hosting and costs than most closed models.
- Palantir CEO Alex Karp recently went viral discussing this dynamic on CNBC, saying frontier AI tools from closed model providers are too expensive and don't offer enough clarity on IP protections.
Flashback: This isn't Murati's first go-round with the open/closed model dilemma.
- She was at OpenAI in 2019 when the lab — founded on a promise of openness — withheld the full version of GPT-2 over misuse fears, heralding the company's retreat from fully open releases.
- Just because Inkling is open weight, that doesn't mean the rest of Thinking Machines' models will be. Her current strategy could mirror that case-by-case logic: release models openly when the risks are manageable and hold them back when they aren't.
Follow the money: Thinking Machines raised a record $2 billion seed round at a $12 billion valuation in 2025, before it had released a model or product.
- Nvidia was among the startup's investors and has since deepened the relationship.
- Thinking Machines also reportedly signed a multibillion-dollar Google Cloud deal.
The bottom line: Inkling is Thinking Machines' first real test of whether its billions in funding can translate into a compelling alternative for enterprises looking to customize AI.
