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DeepSeek R1 Distill Qwen 7B vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Qwen 7B leads with 12.3% higher average benchmark score. Overall, DeepSeek R1 Distill Qwen 7B is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-R1-Distill-Qwen-7B was developed as a compact distilled model, designed to provide reasoning capabilities in an efficient 7B parameter package. Built to extend analytical AI to a broad range of applications, it balances capability with the practical benefits of a smaller model size.
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Microsoft
Phi-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
5 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
DeepSeek R1 Distill Qwen 7B
DeepSeek
2025-01-20
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Average performance across 1 common benchmarks
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DeepSeek R1 Distill Qwen 7B
Average Score:49.1%(+12.3%)
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Phi-3.5-MoE-instruct
Average Score:36.8%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek R1 Distill Qwen 7B
0 providers
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Phi-3.5-MoE-instruct
0 providers
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DeepSeek R1 Distill Qwen 7B
Avg Score:49.1%(+12.3%)
Providers:0
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Phi-3.5-MoE-instruct
Avg Score:36.8%
Providers:0