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Mistral Small 3.1 24B Base vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Mistral Small 3.1 24B Base leads with 4.5% higher average benchmark score. Mistral Small 3.1 24B Base supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small 3.1 24B Base represents an updated iteration of the 24B foundation model, developed with architectural refinements and improved training. Built to provide enhanced base capabilities for fine-tuning, it incorporates learnings from previous versions for better downstream performance.
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Microsoft
Phi-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
6 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:58.2%(+4.5%)
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Phi-3.5-MoE-instruct
Average Score:53.7%
Provider Availability & Performance
Available providers and their performance metrics
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Mistral Small 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Phi-3.5-MoE-instruct
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Mistral Small 3.1 24B Base
Avg Score:58.2%(+4.5%)
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:53.7%
Providers:0