MoonshotAi

Kimi K2 Thinking

MoonshotAiBalanced
ThinkingTool UseStructured Output

About this model

Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in Kimi K2, it activates 32 billion parameters per forward pass and supports 256 k-token context windows. The model is optimized for persistent step-by-step thought, dynamic tool invocation, and complex reasoning workflows that span hundreds of turns. It interleaves step-by-step reasoning with tool use, enabling autonomous research, coding, and writing that can persist for hundreds of sequential actions without drift. It sets new open-source benchmarks on HLE, BrowseComp, SWE-Multilingual, and LiveCodeBench, while maintaining stable multi-agent behavior through 200–300 tool calls. Built on a large-scale MoE architecture with MuonClip optimization, it combines strong reasoning depth with high inference efficiency for demanding agentic and analytical tasks.

Performance Tier

Balanced

Kimi K2 Thinking is a balanced model from MoonshotAi : strong performance at a reasonable price.

Strong cost-performance ratio. Reliable for most professional use cases without premium pricing.

Pricing

This model is included in Elosia plans
Typeper 1M tokens
Input (prompt)$0.470
Output (completion)$2.00
Cache read$0.141

Capabilities

Context Length131K
Max Output Tokens
TokenizerOther
Inputtext
Outputtext
Release DateNovember 6, 2025

Benchmarks

General Intelligence
MMLU
84%
GPQA Diamond
60.5%
Mathematics
MATH-500
88%
Programming
HumanEval
84%

Recommended Use Cases

MathematicsAnalysisResearchCoding

Strengths

  • Extended thinking mode for complex reasoning tasks
  • Strong mathematical reasoning capabilities
  • Transparent chain-of-thought process

Limitations

  • Slower than standard Kimi K2 due to thinking overhead
  • Less suited for quick conversational interactions

Resources

This model may use your data for training

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