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GPT-4.1 nano vs Llama 3.2 90B Instruct
Comprehensive side-by-side LLM comparison
Llama 3.2 90B Instruct leads with 2.1% higher average benchmark score. GPT-4.1 nano offers 824.3K more tokens in context window than Llama 3.2 90B Instruct. Both models have similar pricing. Llama 3.2 90B Instruct is available on 5 providers. 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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Meta
Llama 3.2 90B was developed as a flagship-tier open-source model, designed to provide advanced capabilities with 90 billion parameters. Built to serve applications requiring high-quality reasoning and generation, it represents a powerful option within the Llama 3.2 series for demanding tasks.
6 months newer
Llama 3.2 90B 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($0.25 cheaper)
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Llama 3.2 90B Instruct
Input:$0.35
Output:$0.40
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%
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Llama 3.2 90B Instruct
Average Score:62.6%(+2.1%)
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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 90B Instruct
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GPT-4.1 nano
Avg Score:60.5%
Providers:1
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Llama 3.2 90B Instruct
Avg Score:62.6%(+2.1%)
Providers:5