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DeepSeek-V3 vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 20.8% higher average benchmark score. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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.
4 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
DeepSeek-V3
DeepSeek
2024-12-25
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V3
Average Score:74.5%(+20.8%)
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Phi-3.5-MoE-instruct
Average Score:53.7%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Phi-3.5-MoE-instruct
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DeepSeek-V3
Avg Score:74.5%(+20.8%)
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:53.7%
Providers:0