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DeepSeek-V2.5 vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-V2.5 leads with 15.9% higher average benchmark score. DeepSeek-V2.5 is available on 3 providers. Overall, DeepSeek-V2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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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.
3 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
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Performance Metrics
Context window and performance specifications
Average performance across 5 common benchmarks
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DeepSeek-V2.5
Average Score:83.1%(+15.9%)
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Phi-3.5-MoE-instruct
Average Score:67.1%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:83.1%(+15.9%)
Providers:3
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Phi-3.5-MoE-instruct
Avg Score:67.1%
Providers:0