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GPT-4.1 nano vs Llama 3.2 11B Instruct
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 8.5% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Llama 3.2 11B Instruct. Both models have similar pricing. Llama 3.2 11B Instruct is available on 6 providers. 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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Meta
Llama 3.2 11B was introduced as a mid-sized variant in the Llama 3.2 family, designed to offer enhanced capabilities while maintaining efficiency. Built to provide a balanced option for applications requiring more than lightweight models but less than flagship sizes, it serves diverse use cases in the open-source community.
6 months newer
Llama 3.2 11B Instruct
Meta
2024-09-25
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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GPT-4.1 nano
Input:$0.10
Output:$0.40
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Llama 3.2 11B Instruct
Input:$0.05
Output:$0.05($0.40 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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GPT-4.1 nano
Average Score:60.5%(+8.5%)
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Llama 3.2 11B Instruct
Average Score:52.0%
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Knowledge Cutoff
Training data recency comparison
Llama 3.2 11B Instruct
2023-12-31
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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Llama 3.2 11B Instruct
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GPT-4.1 nano
Avg Score:60.5%(+8.5%)
Providers:1
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Llama 3.2 11B Instruct
Avg Score:52.0%
Providers:6