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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-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
1 year newer
Qwen2.5-Coder 7B 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 7B Instruct
Minimax M 2.5
Qwen2.5-Coder 7B Instruct
Minimax M 2.5
Qwen2.5-Coder 7B Instruct