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
Qwen2.5-7B-Instruct is a 7-billion-parameter open-weight language model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens with improved code, math, and multilingual coverage. The model delivers significantly stronger instruction-following, structured output generation, and long-context handling compared to its predecessor, supporting 128K context windows in a compact form factor. It became widely adopted as a foundation for fine-tuning, RAG pipelines, and on-device deployment due to its balance of capability and efficiency.
1 year newer
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19
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 7B Instruct
Minimax M 2.5
Qwen2.5 7B Instruct
Minimax M 2.5
Qwen2.5 7B Instruct