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Comprehensive side-by-side LLM comparison
Minimax M 2.5 leads with 2.3% higher average benchmark score. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
Zhipu AI
GLM-4.7, released by Zhipu AI on December 22, 2025, is a large language model with approximately 400 billion parameters from the GLM-4 family, designed for deep mathematical reasoning, multi-file software engineering, and stable agentic orchestration. It features a 200K token context window and 128K maximum output tokens, supporting extended code and analysis generation. GLM-4.7 targets advanced open-source deployments under an MIT license via Zhipu AI's Z.ai platform.
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
GLM-4.7
Zhipu AI
2025-12-22
Minimax M 2.5
MiniMax
2026-02-13
Cost per million tokens (USD)
GLM-4.7
Minimax M 2.5
Context window and performance specifications
Average performance across 2 common benchmarks
GLM-4.7
Minimax M 2.5
Performance comparison across key benchmark categories
GLM-4.7
Minimax M 2.5
Available providers and their performance metrics
GLM-4.7
Zhipu AI
Minimax M 2.5
MiniMax
GLM-4.7
Minimax M 2.5
GLM-4.7
Minimax M 2.5