Moonshot AI Releases Kimi K3.1 Pro Open-Source Multimodal Agent Model
Moonshot AI has released Kimi K3.1 Pro, the first model in the K3.1 series. It uses a MoE architecture with 896 experts, activating 16 per token, supports a 1-million-token context window, and its weights are open-sourced in MXFP4 quantization. The model was post-trained from Kimi K3 via large-scale joint reinforcement learning across hundreds of downstream domains, and shows clear improvements in agentic capabilities such as coding, 3D creation, financial research, and factual accuracy. The API is now live at platform.kimi.ai under the model name kimi-k3.1-pro, offering OpenAI/Anthropic-compatible interfaces, with reasoning_effort supporting three levels—low, high, and max—defaulting to max.
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SelectedAI score 85
The original text provides the full architecture parameters and comparisons across dozens of benchmarks, which can be used to assess where this open-source multimodal agent model stands on coding and long-context tasks.