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Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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.
Alibaba / Qwen
Qwen2.5-Coder-32B-Instruct is a 32-billion-parameter code-specialized model from Alibaba, released in November 2024 and trained on a large corpus spanning 92 programming languages including C, Python, Java, Rust, and domain-specific languages. The model was designed to provide competitive code generation, repair, and reasoning capabilities as an open-weight alternative for developers building code assistant tools and automated review pipelines. Its 128K context window enables whole-file and multi-file code comprehension, making it particularly suited for complex repository-level tasks.
1 year newer
Qwen2.5-Coder 32B Instruct
Alibaba / Qwen
2024-11-12
Minimax M 2.5
MiniMax
2026-02-13
Context window and performance specifications
Available providers and their performance metrics
Minimax M 2.5
MiniMax
Qwen2.5-Coder 32B Instruct
Minimax M 2.5
Qwen2.5-Coder 32B Instruct
Minimax M 2.5
Qwen2.5-Coder 32B Instruct