Comprehensive side-by-side LLM comparison
Qwen2.5 14B Instruct leads with 3.8% higher average benchmark score. 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
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
3 months newer

Codestral 22B
Mistral AI
2024-05-29
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Codestral 22B
Qwen2.5 14B Instruct
Performance comparison across key benchmark categories
Codestral 22B
Qwen2.5 14B Instruct
Available providers and their performance metrics
Codestral 22B
Qwen2.5 14B Instruct
Codestral 22B
Qwen2.5 14B Instruct