Kimi K3.1 Pro: open-weight model nears Claude Opus 5.5
Why it matters
Kimi K3.1 Pro is Kimi's most capable 3T-class open-weight model so far: a mixture-of-experts model with 2.8T total and 104B active parameters, a 1-million-token context window and multimodal input. By Kimi's own numbers it scores 65.7% on Terminal-Bench 4.0, ahead of GPT-6 Astra (58.2%) and narrowly behind Claude Opus 5.5 (66.4%), and tops Kimi's SWE Marathon chart at 51.7 (Opus 5.5: 46.3). In one internal long-horizon test it built a human walking simulator, found and corrected 36 errors in shoulder-muscle moment-arm calculations, and got the simulated human walking for 11.2 seconds. On Kimi's hard hallucination stress test, the claim-level error rate fell from 23.4% (K3) to 8.3%. For the open-weight release Kimi removed cyber-related training data: on its internal exploit benchmark the unfiltered checkpoint solved 90.5% versus 81.0% for the final model. A Highspeed version runs 2-3x faster; both are live on Kimi.ai, Kimi Work, Kimi Code and the Kimi API, with full weights due by Nov 4. Caveat: these are Kimi's own benchmark results, and the weights aren't public yet.
Read the source: Kimi (tech blog) (opens in a new tab)
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