Comprehensive side-by-side LLM comparison
Phi-3.5-MoE Instruct leads with 2.6% 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.
Microsoft
Phi-3.5-MoE-instruct is a sparse mixture-of-experts model from Microsoft's Phi research team, released in August 2024 with 42 billion total parameters across 16 experts and approximately 6.6 billion active parameters per forward pass. The model applies Microsoft's small-data, high-quality training philosophy — developed across earlier Phi generations — to a MoE architecture, targeting reasoning quality comparable to much larger dense models at a fraction of the inference compute. Released under the MIT license, it was notable in the research community for demonstrating that MoE efficiency gains could be realized at smaller total parameter counts than typical large-scale MoE deployments.
2 months newer

Codestral 22B
Mistral AI
2024-05-29

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
Average performance across 1 common benchmarks
Codestral 22B
Phi-3.5-MoE Instruct
Performance comparison across key benchmark categories
Codestral 22B
Phi-3.5-MoE Instruct
Available providers and their performance metrics
Codestral 22B
Phi-3.5-MoE Instruct
Codestral 22B
Phi-3.5-MoE Instruct