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DeepSeek R1 Distill Llama 70B vs QwQ-32B
Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Llama 70B leads with 1.3% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1-Distill-Llama-70B was created through knowledge distillation from DeepSeek-R1 into a Llama-based architecture, designed to transfer reasoning capabilities to a widely-used open-source foundation. Built to combine DeepSeek's reasoning innovations with Llama's ecosystem compatibility, it enables broader access to advanced reasoning techniques.
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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 Llama 70B
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 Llama 70B
Average Score:76.0%(+1.3%)
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QwQ-32B
Average Score:74.7%
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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 Llama 70B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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QwQ-32B
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DeepSeek R1 Distill Llama 70B
Avg Score:76.0%(+1.3%)
Providers:1
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QwQ-32B
Avg Score:74.7%
Providers:0