Moonshot's 2.8T-parameter Kimi K3 weights land on Hugging Face

Moonshot AI has published Kimi K3's full 2.8-trillion-parameter weights under the Kimi K3 License — the largest open-weight model release to date.

Moonshot AI released the full weights of Kimi K3 at 00:00 UTC on July 27, uploading roughly 1.4 terabytes of MXFP4-quantized checkpoints to its Hugging Face organization under the custom Kimi K3 License. At 2.8 trillion total parameters, it is the largest open-weight model ever published.

A frontier-scale system, now downloadable

K3 is a mixture-of-experts model built on Moonshot's Stable LatentMoE framework, activating 16 of its 896 experts per token, with a 1-million-token context window and native vision. By Moonshot's own accounting it still trails Anthropic's Claude Fable 5 and OpenAI's GPT-5.6 Sol on overall capability, but it beats Claude Opus 4.8 and GPT-5.5 across the company's coding and agentic evaluations; Tom's Hardware also flagged a win over Fable 5 on the Frontend Code Arena benchmark. The model has been serving traffic through Moonshot's API — OpenAI- and Anthropic-compatible endpoints at roughly $3 per million input tokens and $15 per million output — so what changed this weekend is not access but control: anyone can now run it on their own hardware. In practice, the 1.4TB footprint confines self-hosting to large teams and infrastructure providers, at least until smaller community quantizations appear.

Released into a political storm

The timing is pointed. Washington is reportedly weighing selective bans on Chinese open-weight models, a UK–US joint assessment of K3's cyber capabilities landed days ago, and the "Open Weights and American AI Leadership" letter urging the US to spare open models has doubled since its July 24 launch to roughly 50 signatories — Nvidia, Microsoft and Meta from the founding group, with Google and OpenAI added later; Anthropic and Amazon have stayed off every version. Hugging Face greeted the drop with a three-word post — "free the parameters" — while Moonshot itself is pursuing a Hong Kong IPO at a reported $50 billion valuation, making the release a statement of momentum as much as of openness.

The release matters because it converts a policy abstraction into a fact on the ground: any organization with the hardware can now serve a near-frontier model locally, without touching a Chinese API. That simultaneously defuses the data-sovereignty argument against Chinese AI and undercuts any regulatory approach that assumes frontier capability can be contained at the API layer.

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