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Phi 4 Reasoning vs QwQ-32B
Comprehensive side-by-side LLM comparison
QwQ-32B leads with 3.4% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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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.
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Alibaba Cloud / Qwen Team
QwQ 32B was developed as a reasoning-focused model, designed to emphasize analytical thinking and problem-solving capabilities. Built with 32 billion parameters optimized for step-by-step reasoning, it demonstrates Qwen's exploration into models that prioritize deliberate analytical processing.
1 month newer
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
Phi 4 Reasoning
Microsoft
2025-04-30
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Average performance across 4 common benchmarks
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Phi 4 Reasoning
Average Score:69.6%
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QwQ-32B
Average Score:73.0%(+3.4%)
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Knowledge Cutoff
Training data recency comparison
QwQ-32B
2024-11-28
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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Phi 4 Reasoning
0 providers
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QwQ-32B
0 providers
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Phi 4 Reasoning
Avg Score:69.6%
Providers:0
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QwQ-32B
Avg Score:73.0%(+3.4%)
Providers:0