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GPT-5 nano vs Phi 4
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 15.1% higher average benchmark score. GPT-5 nano offers 496.0K more tokens in context window than Phi 4. Both models have similar pricing. GPT-5 nano supports multimodal inputs. 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-4 was introduced as the fourth generation of Microsoft's small language model series, designed to push the boundaries of what compact models can achieve. Built with advanced training techniques and architectural improvements, it demonstrates continued progress in efficient, high-quality language models.
7 months newer
Phi 4
Microsoft
2024-12-12
GPT-5 nano
OpenAI
2025-08-07
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Pricing Comparison
Cost per million tokens (USD)
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GPT-5 nano
Input:$0.05
Output:$0.40
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Phi 4
Input:$0.07
Output:$0.14($0.24 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-5 nano
Average Score:71.2%(+15.1%)
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Phi 4
Average Score:56.1%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
Phi 4
2024-06-01
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%(+15.1%)
Providers:2
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Phi 4
Avg Score:56.1%
Providers:1