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DeepSeek R1 Distill Qwen 32B vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Qwen 32B leads with 31.7% higher average benchmark score. 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-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
5 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
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-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.10 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%(+31.7%)
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Phi-3.5-mini-instruct
Average Score:30.4%
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-3.5-mini-instruct
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DeepSeek R1 Distill Qwen 32B
Avg Score:62.1%(+31.7%)
Providers:1
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Phi-3.5-mini-instruct
Avg Score:30.4%
Providers:1