2天前
· Decrypt
Mira Murati Drops Her First AI Model After Leaving OpenAI—And It's Fully Open Source
Mira Murati left OpenAI in September 2024 to do her own thing. Almost two years later, that exploration shipped. Thinking Machines Lab, the company she founded, released <a href="https://thinkingmachines.ai/news/introducing-inkling/" target="_blank" rel="nofollow external noopener" class="sc-adb616fe-0 bJsyml">>Inkling</a>—a multimodal AI model trained entirely from scratch, with every weight available for free download.
When OpenAI's board <a href="https://decrypt.co/206531/sam-altman-out-as-ceo-of-openai-was-not-consistently-candid-with-company-board" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">fired Sam Altman in November 2023</a>, Murati—then CTO—was named interim CEO. Altman was reinstated five days later, Murati returned to CTO, then left for good roughly 10 months after that. She founded Thinking Machines Lab in February 2025.
The company then went quiet—and rich. It raised $2 billion at a $12 billion valuation in July 2025, led by Andreessen Horowitz with Nvidia, Accel, ServiceNow, Cisco, AMD, and Jane Street alongside—one of the largest seed rounds in Silicon Valley history <a href="https://techcrunch.com/2025/07/15/mira-muratis-thinking-machines-lab-is-worth-12b-in-seed-round/" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">at the time</a>.
Reports in November 2025 had the company seeking a new round at a $50 billion valuation. Those talks <a href="https://www.nytimes.com/2026/01/22/technology/thinking-machines-ai-startup-openai.html" target="_blank" class="sc-adb616fe-0 bJsyml" rel="nofollow">collapsed</a> by January 2026.
Inkling is a mixture-of-experts model—an architecture where only a portion of the network activates for any given input, keeping inference fast without sacrificing depth. It is a very big model: It has 975 billion total parameters (the internal settings that define how the model processes information), with 41 billion active per task, so forget about running it on your local machine.
Being multimodal, this model accepts text, images, and audio, and supports a context window—the amount of text the model can reason over at once—of 1 million tokens, roughly 750,000 words. It was pretrained on 45 trillion tokens spanning text, images, audio, and video.
"Our first model, Inkling. Trained from scratch, weights are open, fine-tunable on Tinker today," Murati wrote on X . The fact that it’s trained from scratch means a lot, especially in the open-source community as it could bring a breath of fresh air to Western developers that are wary of China but need to use Asian models for their developments because the top AI companies in the Western world are mostly focused on shipping close-source models.
Fine-tuning is the process of retraining an existing model on a specialized dataset to improve its performance on a specific task. Tinker is Thinking Machines' cloud platform built around that use case. The full weights are also on <a href="https://huggingface.co/thinkingmachines/inkling" target=