Moonshot AI releases open-weight Kimi K3.1 Pro with 2.8T parameters and 1M context

Moonshot AI released Kimi K3.1 Pro on 4 November 2026, publishing open weights on Hugging Face under the custom Kimi K3.1 Pro License alongside a hosted Kimi K3.1 Pro Highspeed tier running 2 to 3 times faster across Kimi.ai, Kimi Work, Kimi Code and the Kimi API (kimi-k3.1-pro).

The multimodal mixture-of-experts (MoE) architecture totals 2.8 trillion parameters with 104 billion activated per token across 896 routed experts (16 routed plus 2 shared per token) paired with a 401-million-parameter MoonViT-V2 native-resolution vision encoder over a 1,048,576-token context window. Across its 93 layers, Moonshot AI pairs 69 Kimi Delta Attention layers with 24 Gated DeepSeek Sparse Attention layers, replacing Gated Multi-head Latent Attention to cut long-context memory overhead. Quantisation-aware training produces native MXFP4 expert weights and MXFP8 activations directly in the published checkpoint.

Agentic coding and 3D CAD benchmarks

Evaluated at maximum thinking effort, Kimi K3.1 Pro leads Claude Opus 5.5 and GPT-6 Astra on long-horizon repository tasks in SWE Marathon v1.1 (51.7 versus 46.3 and 42.5) and Humanity’s Last Exam Full with tools (70.0 versus 67.7 and 57.2), while trailing Opus 5.5 by 0.7 points on Terminal-Bench 4.0 (65.7 versus 66.4, ahead of 58.2 for GPT-6 Astra). Combined with FreeCAD and Blender tool loops, the model scored 92.7 on BenchCAD, reconstructing multi-part assemblies such as turbofan engines from visual inspection. Moonshot AI did not print updated per-token API pricing in its launch post.