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GPT-5 nano vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
GPT-5 nano offers 272.0K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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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 Multimodal was created to handle multiple input modalities including text, images, and potentially other formats. Built to extend Phi-4's efficiency into multimodal applications, it demonstrates that compact models can successfully integrate diverse information types.
6 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
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-multimodal-instruct
Input:$0.05
Output:$0.10($0.30 cheaper)
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
Phi-4-multimodal-instruct
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:0.0%
Providers:2
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Phi-4-multimodal-instruct
Avg Score:0.0%
Providers:1