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Mistral Small 3 24B Base vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Mistral Small 3 24B Base leads with 3.1% 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 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
5 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Mistral Small 3 24B Base
Mistral AI
2025-01-30
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Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Mistral Small 3 24B Base
Average Score:65.3%(+3.1%)
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Phi-3.5-mini-instruct
Average Score:62.2%
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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-mini-instruct
1 providers
Azure
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Mistral Small 3 24B Base
Avg Score:65.3%(+3.1%)
Providers:0
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Phi-3.5-mini-instruct
Avg Score:62.2%
Providers:1