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Magistral Small 2506 vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 1.2% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Magistral Small was created as an efficient reasoning-focused variant, designed to bring analytical capabilities to applications with tighter resource constraints. Built to balance problem-solving depth with practical deployment needs, it extends reasoning-enhanced AI to broader use cases.
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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
Phi 4 Reasoning
Microsoft
2025-04-30
Magistral Small 2506
Mistral AI
2025-06-10
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Average performance across 4 common benchmarks
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Magistral Small 2506
Average Score:63.2%
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Phi 4 Reasoning
Average Score:64.5%(+1.2%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
Magistral Small 2506
2025-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Magistral Small 2506
0 providers
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Phi 4 Reasoning
0 providers
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Magistral Small 2506
Avg Score:63.2%
Providers:0
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Phi 4 Reasoning
Avg Score:64.5%(+1.2%)
Providers:0