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DeepSeek R1 Distill Qwen 32B vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Both models have similar pricing. Phi-4-multimodal-instruct supports multimodal inputs. 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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Microsoft
Phi-4 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
12 days newer
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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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-multimodal-instruct
Input:$0.05
Output:$0.10($0.15 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Phi-4-multimodal-instruct
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-multimodal-instruct
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DeepSeek R1 Distill Qwen 32B
Avg Score:0.0%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1