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Moonshot Releases Kimi K3.1 Pro Weights for Self-Hosting

AI · First reported 4 Nov, 15:30 · Updated 16:31

Image: Wikimedia Commons · NASA Johnson Space Center / Jonny Kim · Public domain

Moonshot AI has published Kimi K3.1 Pro’s weights after first offering the model through its API. The release enables inspection, fine-tuning and self-hosting, but the article says deployment requires substantial hardware and that teams should check the license before use.

  • Moonshot says K3.1 Pro keeps the Kimi K3 architecture and uses additional post-training compute, including reinforcement learning across hundreds of domains.
  • Moonshot-reported coding benchmarks show mixed comparisons: K3.1 Pro scored 65.7 on Terminal-Bench 4.0 versus Claude Opus 5.5’s 66.4, and 51.7 on SWE-Marathon versus 46.3. The article cautions that harness and tool differences limit model-only conclusions.
  • The weights can be self-hosted, but their reported size is about 5.6 TB in BF16 or 2.8 TB at 8-bit precision, before runtime overhead. The article says K3.1 Pro’s separate license had not been announced at publication.
Summary written by Lux AI from 2 articlesUnverified

Key facts

Weights published
Moonshot AI published Kimi K3.1 Pro weights on Hugging Face.
Model size
Approximately 2.8 trillion total parameters and 104 billion active parameters per token.
Context window
1,048,576 tokens.
Weight storage estimate
About 5.6 TB in BF16 or 2.8 TB at 8-bit precision, before runtime overhead and the key-value cache.
API launch date and prices
October 23, 2026; $2 per million input tokens and $10 per million output tokens.
Thinking mode
The API accepts thinking-mode requests exclusively; disabling thinking returns HTTP 400, according to the article.

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