Moonshot AI Releases Kimi K3.1 Pro: 2.8T-Parameter MoE Model With 1M Context Window

Moonshot AI has released Kimi K3.1 Pro, an open-weight mixture-of-experts model featuring 2.8 trillion total parameters with 104 billion active parameters per forward pass and a 1 million token context window. The MoE architecture means inference costs remain tractable despite the massive total parameter count, making this competitive with frontier closed models on long-context reasoning tasks. The 1M context window is particularly significant for developers building document-heavy or multi-turn agentic pipelines where maintaining long conversational or retrieval context is critical. Being open-weight, Kimi K3.1 Pro can be self-hosted, giving teams control over data privacy and inference costs in a way that closed API models do not. This release continues the trend of Chinese AI labs pushing open-weight models that match or challenge proprietary Western counterparts on scale and capability.