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GPT-4.1 nano vs Phi-3.5-vision-instruct
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 12.4% higher average benchmark score. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
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OpenAI
GPT-4.1 Nano was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
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Microsoft
Phi-3.5 Vision was developed as a multimodal variant of Phi-3.5, designed to understand and reason about both images and text. Built to extend the Phi family's efficiency into vision-language tasks, it enables compact multimodal AI for practical applications.
7 months newer
Phi-3.5-vision-instruct
Microsoft
2024-08-23
GPT-4.1 nano
OpenAI
2025-04-14
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT-4.1 nano
Average Score:55.8%(+12.4%)
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Phi-3.5-vision-instruct
Average Score:43.5%
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
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-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Phi-3.5-vision-instruct
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GPT-4.1 nano
Avg Score:55.8%(+12.4%)
Providers:1
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Phi-3.5-vision-instruct
Avg Score:43.5%
Providers:0