Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
Mistral AI
Codestral is a 22-billion-parameter code-specialized model from Mistral AI, released in May 2024 as the company's first dedicated coding model, trained with focus on fill-in-the-middle (FIM) completion, code generation, and repair across 80+ programming languages. Unlike Mistral's general-purpose Apache 2.0 models, Codestral was released under a separate non-production research license, reflecting its positioning as a professional coding tool requiring commercial API access for production deployment. Its FIM support made it particularly valued for IDE integrations and code completion tools that need to insert code within existing contexts rather than only appending to the end.
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.
3 months newer

Codestral 22B
Mistral AI
2024-05-29
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Codestral 22B
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Codestral 22B
Qwen2.5 7B Instruct
Available providers and their performance metrics
Codestral 22B
Qwen2.5 7B Instruct
Codestral 22B
Qwen2.5 7B Instruct