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Comprehensive side-by-side LLM comparison
Minimax M 2.5 leads with 2.5% higher average benchmark score. Kimi K2.5 offers 60.1K more tokens in context window than Minimax M 2.5. Minimax M 2.5 is $6.00 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2.5, released by Moonshot AI in January 2026, is an updated Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters. It builds on Kimi K2 with improved coding performance across multiple languages and an expanded context window. Kimi K2.5 targets agentic development workflows, polyglot code generation, and open-source deployments requiring large-scale MoE reasoning.
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.
1 month newer
Kimi K2.5
Moonshot AI
2026-01
Minimax M 2.5
MiniMax
2026-02-13
Cost per million tokens (USD)
Kimi K2.5
Minimax M 2.5
Context window and performance specifications
Average performance across 2 common benchmarks
Kimi K2.5
Minimax M 2.5
Performance comparison across key benchmark categories
Kimi K2.5
Minimax M 2.5
Available providers and their performance metrics
Kimi K2.5
Moonshot AI
Minimax M 2.5
MiniMax
Kimi K2.5
Minimax M 2.5
Kimi K2.5
Minimax M 2.5