Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
Mistral AI
Devstral 2, released by Mistral AI on December 9, 2025, is a 123 billion parameter dense transformer model specifically designed for software engineering tasks. It features a 256K token context window and achieved 72.2% on SWE-bench Verified at release, making it a competitive open-weight option for automated coding and agentic development. Devstral 2 targets code generation, multi-file software engineering, and agentic development workflows under a modified MIT license.
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.
1 year newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22

Devstral-2-123B
Mistral AI
2025-12-09
Context window and performance specifications
Available providers and their performance metrics
Devstral-2-123B
OpenRouter
Phi-3.5-MoE Instruct
Devstral-2-123B
Phi-3.5-MoE Instruct
Devstral-2-123B
Phi-3.5-MoE Instruct