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Gemma 3 4B vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 1.9% higher average benchmark score. GPT-4.1 nano offers 818.2K more tokens in context window than Gemma 3 4B. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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Gemma 3 4B was developed as a compact yet capable open-source model, designed to strike a balance between performance and resource efficiency. Built with 4 billion parameters and instruction tuning, it provides a practical option for applications requiring moderate capability with manageable computational costs.
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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.
1 month newer
Gemma 3 4B
2025-03-12
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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Gemma 3 4B
Input:$0.02
Output:$0.04($0.44 cheaper)
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GPT-4.1 nano
Input:$0.10
Output:$0.40
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Gemma 3 4B
Average Score:60.5%
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GPT-4.1 nano
Average Score:62.4%(+1.9%)
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
Gemma 3 4B
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 3 4B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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GPT-4.1 nano
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Gemma 3 4B
Avg Score:60.5%
Providers:1
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GPT-4.1 nano
Avg Score:62.4%(+1.9%)
Providers:1