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Mistral Small 3 24B Base vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 3.4% higher average benchmark score. Mistral Small 3 24B Base supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small 24B Base was developed as a 24-billion-parameter foundation model, designed to serve as a base for fine-tuning and customization. Built to provide a strong starting point for domain-specific applications, it represents an intermediate-scale option in Mistral's model lineup.
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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.
5 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Mistral Small 3 24B Base
Mistral AI
2025-01-30
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Average performance across 7 common benchmarks
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Mistral Small 3 24B Base
Average Score:65.3%
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Phi-3.5-MoE-instruct
Average Score:68.7%(+3.4%)
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Knowledge Cutoff
Training data recency comparison
Mistral Small 3 24B Base
2023-10-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Mistral Small 3 24B Base
0 providers
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Phi-3.5-MoE-instruct
0 providers
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Mistral Small 3 24B Base
Avg Score:65.3%
Providers:0
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Phi-3.5-MoE-instruct
Avg Score:68.7%(+3.4%)
Providers:0