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DeepSeek-R1-0528 vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
DeepSeek-R1-0528 leads with 42.0% higher average benchmark score. DeepSeek-R1-0528 is available on 3 providers. Overall, DeepSeek-R1-0528 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-R1-0528 represents a specific release iteration of the DeepSeek-R1 model, developed to incorporate refinements and improvements from ongoing training. Built to provide enhanced reasoning capabilities based on accumulated insights, it continues the evolution of DeepSeek's reasoning-focused architecture.
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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.
9 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
DeepSeek-R1-0528
DeepSeek
2025-05-28
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-R1-0528
Average Score:83.0%(+42.0%)
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Phi-3.5-MoE-instruct
Average Score:41.0%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1-0528
3 providers
DeepInfra
Throughput: 45.04 tok/s
Latency: 0.61ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Novita
Throughput: 37.96 tok/s
Latency: 1.18ms
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DeepSeek-R1-0528
Avg Score:83.0%(+42.0%)
Providers:3
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Phi-3.5-MoE-instruct
Avg Score:41.0%
Providers:0