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GPT-5 nano vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 34.4% higher average benchmark score. GPT-5 nano supports multimodal inputs. GPT-5 nano is available on 2 providers. Overall, GPT-5 nano is the stronger choice for coding tasks.
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OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
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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.
11 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
GPT-5 nano
OpenAI
2025-08-07
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-5 nano
Average Score:71.2%(+34.4%)
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Phi-3.5-MoE-instruct
Average Score:36.8%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-5 nano
2 providers
OpenAI
Throughput: 500 tok/s
Latency: 0.3ms
ZeroEval
Throughput: 500 tok/s
Latency: 0.3ms
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GPT-5 nano
Avg Score:71.2%(+34.4%)
Providers:2
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Phi-3.5-MoE-instruct
Avg Score:36.8%
Providers:0