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Mistral Small vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Mistral Small was created as an efficient model offering, designed to provide capable language understanding with reduced computational requirements. Built to serve cost-sensitive applications while maintaining quality, it enables Mistral's technology in scenarios where resource efficiency is valued.
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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.
7 months newer
Mistral Small
Mistral AI
2024-09-17
Phi 4 Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
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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
1 providers
Mistral AI
Throughput: 0.1 tok/s
Latency: 0.5ms
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Phi 4 Reasoning
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Mistral Small
Avg Score:0.0%
Providers:1
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Phi 4 Reasoning
Avg Score:0.0%
Providers:0