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Comprehensive side-by-side LLM comparison
Kimi K2 Thinking leads with 4.2% higher average benchmark score. Kimi K2 Thinking offers 60.1K more tokens in context window than Minimax M 2.5. Minimax M 2.5 is $3.50 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2 Thinking, released by Moonshot AI on November 6, 2025, is a reasoning-focused variant of Kimi K2 with 1 trillion total parameters and 32 billion active parameters, featuring extended chain-of-thought processing for complex problem solving. It builds on K2's agentic coding strengths with additional capabilities for mathematical and scientific reasoning. Kimi K2 Thinking targets open-source deployments requiring deep, deliberate reasoning across coding and analytical domains.
MiniMax
MiniMax M2.5 is a large language model from MiniMax extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. It targets agentic tool use, coding automation, and office productivity tasks, with strong results on software engineering and web browsing benchmarks. M2.5 represents the next generation of MiniMax's M-series models optimized for production agentic workloads.
3 months newer
Kimi K2 Thinking
Moonshot AI
2025-11-06
Minimax M 2.5
MiniMax
2026-02-13
Cost per million tokens (USD)
Kimi K2 Thinking
Minimax M 2.5
Context window and performance specifications
Average performance across 1 common benchmarks
Kimi K2 Thinking
Minimax M 2.5
Performance comparison across key benchmark categories
Kimi K2 Thinking
Minimax M 2.5
Available providers and their performance metrics
Kimi K2 Thinking
Moonshot AI
Minimax M 2.5
MiniMax
Kimi K2 Thinking
Minimax M 2.5
Kimi K2 Thinking
Minimax M 2.5