Kimi K3.1 Pro model weights are out

Moonshot AI released the weights for Kimi K3.1 Pro, a 2.8T-parameter mixture-of-experts model with 104B active parameters, a 1M-token context and MXFP4 quantization-aware training. It swaps K3's full-attention layers for sparse attention to cut long-context cost. Moonshot's own tables show leads on SWE Marathon (51.7) and HLE with tools (70.0), but trailing results on ProgramBench and the cybersecurity exploit tests. Its hallucination benchmark is internal, and none of the figures has been independently verified. The API is OpenAI-compatible, and vLLM and SGLang are supported.