Moonshotai Kimi K2 0905 features MoE architecture and 262k-token context window. Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2). It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k. This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimised for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training. Available at $0.39/1M tokens.
Visit MoonshotAI: Kimi K2 0905AI-Powered
Leverages advanced AI technology to deliver cutting-edge capabilities and results.
Fast & Efficient
Optimized performance ensures quick results without compromising on quality.
Purpose-Built
Specifically designed for llms tasks and workflows.
Moonshotai Model Timeline
262k tokens context
262k tokens context
262k tokens context
33k tokens context
131k tokens context
131k tokens context
Specifications
AI Evaluation
Optimized for programming tasks, this model excels at code generation, debugging, and software engineering workflows with solid benchmark performance.
Pros
- 262k token context window
- Strong code generation and debugging
- Advanced logical reasoning
- Agent-ready with tool use
Cons
- May lack creative flair
- API integration required
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