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Mistral Small 3.1 24B Base vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 14.5% higher average benchmark score. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, Phi 4 Mini Reasoning is the stronger choice for coding tasks.
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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-4 Mini Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
1 month newer
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:37.5%
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Phi 4 Mini Reasoning
Average Score:52.0%(+14.5%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini Reasoning
2025-02-01
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 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Phi 4 Mini Reasoning
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Mistral Small 3.1 24B Base
Avg Score:37.5%
Providers:1
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Phi 4 Mini Reasoning
Avg Score:52.0%(+14.5%)
Providers:0