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GPT-4.1 nano vs Phi 4 Mini Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Mini Reasoning leads with 1.7% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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-4 Mini Reasoning was developed to incorporate extended thinking capabilities into the ultra-compact Phi-4 Mini architecture. Built to demonstrate that reasoning enhancements can be applied even to very small models, it brings analytical depth to resource-constrained environments.
16 days newer
GPT-4.1 nano
OpenAI
2025-04-14
Phi 4 Mini Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-4.1 nano
Average Score:50.3%
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Phi 4 Mini Reasoning
Average Score:52.0%(+1.7%)
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
Phi 4 Mini Reasoning
2025-02-01
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-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Phi 4 Mini Reasoning
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GPT-4.1 nano
Avg Score:50.3%
Providers:1
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Phi 4 Mini Reasoning
Avg Score:52.0%(+1.7%)
Providers:0