MoonshotAI: Kimi K2 0905

Kimi-K2-0905

Kimi K2 0905 is the September update to Kimi K2 0711, a large-scale Mixture-of-Experts (MoE) model developed by Moonshot AI. It features 1 trillion total parameters with 32B active per forward pass and extends long-context inference from 128K to 256K tokens.

This release enhances agentic coding with improved accuracy and better generalization across scaffolds, while also boosting frontend development with more refined and functional outputs for web, 3D, and related applications. Optimized for agentic capabilities—spanning advanced tool use, reasoning, and code synthesis—Kimi K2 continues to excel across benchmarks in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool use (Tau2, AceBench). Training is powered by a novel stack that incorporates the MuonClip optimizer for stable, large-scale MoE performance.

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Creator Moonshot AI
Release Date September, 2025
License Modified MIT License
Context Window 262,144
Image Input Support No
Open Source (Weights) Yes
Parameters 1000B, 32.0B active at inference time
Model Weights Click here

Performance Benchmarks

Benchmark Metric K2-Instruct-0905 K2-Instruct-0711 Qwen3-Coder-480B-A35B-Instruct GLM-4.5 DeepSeek-V3.1 Claude-Sonnet-4 Claude-Opus-4
SWE-Bench verified ACC 69.2 ± 0.63 65.8 69.6* 64.2* 66.0* 72.7* 72.5*
SWE-Bench Multilingual ACC 55.9 ± 0.72 47.3 54.7* 52.7 54.5* 53.3*
Multi-SWE-Bench ACC 33.5 ± 0.28 31.3 32.7 31.7 29.0 35.7
Terminal-Bench ACC 44.5 ± 2.03 37.5 37.5* 39.9* 31.3* 36.4* 43.2*
SWE-Dev ACC 66.6 ± 0.72 61.9 64.7 63.2 53.3 67.1

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