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DeepSeek R1 Distill Qwen 32B vs QwQ-32B
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1-Distill-Qwen-32B was created as a larger distilled variant, designed to transfer more of DeepSeek-R1's reasoning capabilities into a Qwen-based foundation. Built to serve applications requiring enhanced analytical depth, it represents a powerful option in the distilled reasoning model family.
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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
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
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Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek R1 Distill Qwen 32B
Average Score:74.2%
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QwQ-32B
Average Score:74.7%(+0.5%)
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Knowledge Cutoff
Training data recency comparison
QwQ-32B
2024-11-28
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Qwen 32B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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QwQ-32B
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DeepSeek R1 Distill Qwen 32B
Avg Score:74.2%
Providers:1
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QwQ-32B
Avg Score:74.7%(+0.5%)
Providers:0