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Mistral Small 3.1 24B Base vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 23.3% higher average benchmark score. Mistral Small 3.1 24B Base supports multimodal inputs. Overall, Phi 4 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 Reasoning was developed to incorporate extended analytical thinking into the Phi-4 architecture, designed to spend more time on complex problem-solving. Built to combine compact model efficiency with reasoning depth, it represents Microsoft's exploration of thoughtful small models.
1 month newer
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
Phi 4 Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:46.8%
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Phi 4 Reasoning
Average Score:70.0%(+23.3%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
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 Reasoning
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Mistral Small 3.1 24B Base
Avg Score:46.8%
Providers:1
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Phi 4 Reasoning
Avg Score:70.0%(+23.3%)
Providers:0