Comprehensive side-by-side LLM comparison
Phi-3.5-MoE Instruct leads with 6.1% higher average benchmark score. Mistral Small 3.1 24B Instruct supports multimodal inputs. Overall, Phi-3.5-MoE Instruct is the stronger choice for coding tasks.
Mistral AI
Mistral Small 3.1 is a 24-billion-parameter multimodal model from Mistral AI, released in March 2025 as an update to Mistral Small 3 that added vision understanding and expanded the context window from 32K to 128K tokens. The model accepts both text and image inputs, broadening its applicability to document analysis, image-grounded reasoning, and mixed-media workflows without requiring an increase in parameter count. Released under Apache 2.0, it continued Mistral's pattern of incremental capability gains delivered in compact, practically deployable open-weight packages.
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.
6 months newer

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

Mistral Small 3.1 24B Instruct
Mistral AI
2025-03-17
Average performance across 1 common benchmarks
Mistral Small 3.1 24B Instruct
Phi-3.5-MoE Instruct
Performance comparison across key benchmark categories
Mistral Small 3.1 24B Instruct
Phi-3.5-MoE Instruct
Available providers and their performance metrics
Mistral Small 3.1 24B Instruct
Phi-3.5-MoE Instruct
Mistral Small 3.1 24B Instruct
Phi-3.5-MoE Instruct