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DeepSeek R1 Distill Qwen 32B vs Phi 4
Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Qwen 32B leads with 6.0% higher average benchmark score. DeepSeek R1 Distill Qwen 32B offers 224.0K more tokens in context window than Phi 4. Both models have similar pricing. Overall, DeepSeek R1 Distill Qwen 32B is the stronger choice for coding tasks.
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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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Microsoft
Phi-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
1 month newer
Phi 4
Microsoft
2024-12-12
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek R1 Distill Qwen 32B
Input:$0.12
Output:$0.18
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Phi 4
Input:$0.07
Output:$0.14($0.09 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek R1 Distill Qwen 32B
Average Score:62.1%(+6.0%)
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Phi 4
Average Score:56.1%
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Knowledge Cutoff
Training data recency comparison
Phi 4
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Qwen 32B
1 providers
DeepInfra
Throughput: 37 tok/s
Latency: 0.65ms
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Phi 4
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DeepSeek R1 Distill Qwen 32B
Avg Score:62.1%(+6.0%)
Providers:1
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Phi 4
Avg Score:56.1%
Providers:1