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GPT-4.1 nano vs Llama 3.2 3B Instruct
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 10.4% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Llama 3.2 3B Instruct. Both models have similar pricing. GPT-4.1 nano supports multimodal inputs. 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 3B was created as an ultra-compact open-source model, designed to enable on-device and edge deployment scenarios. Built with just 3 billion parameters while retaining instruction-following abilities, it brings Meta's language technology to mobile devices, IoT applications, and resource-constrained environments.
6 months newer
Llama 3.2 3B 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 3B Instruct
Input:$0.01
Output:$0.02($0.47 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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GPT-4.1 nano
Average Score:68.3%(+10.4%)
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Llama 3.2 3B Instruct
Average Score:57.9%
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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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Llama 3.2 3B Instruct
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GPT-4.1 nano
Avg Score:68.3%(+10.4%)
Providers:1
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Llama 3.2 3B Instruct
Avg Score:57.9%
Providers:1