Comprehensive side-by-side LLM comparison
Codestral 22B leads with 5.0% higher average benchmark score. Qwen2.5-Omni-7B supports multimodal inputs. 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-Omni-7B is a 7-billion-parameter end-to-end multimodal model from Alibaba, released in March 2025 as part of the Omni series designed to unify perception and generation across text, images, audio, and video in a single model architecture. Unlike pipeline-based multimodal systems, it processes all modalities end-to-end and can generate both text and speech outputs, targeting use cases in voice assistants, multimodal agents, and real-time interactive applications. Its compact size made it notable for on-device and resource-constrained multimodal deployments.
10 months newer

Codestral 22B
Mistral AI
2024-05-29
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Average performance across 1 common benchmarks
Codestral 22B
Qwen2.5-Omni-7B
Performance comparison across key benchmark categories
Codestral 22B
Qwen2.5-Omni-7B
Available providers and their performance metrics
Codestral 22B
Qwen2.5-Omni-7B
Codestral 22B
Qwen2.5-Omni-7B