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GPT-5 nano vs Llama 3.2 3B Instruct
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 38.4% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Llama 3.2 3B Instruct. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Overall, GPT-5 nano is the stronger choice for coding tasks.
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OpenAI
GPT-5 Nano was developed as the most compact variant in the GPT-5 family, designed for deployment in resource-constrained environments and edge computing scenarios. Built to bring next-generation AI capabilities to devices and applications where latency and efficiency are paramount, it distills GPT-5 innovations into a minimal footprint.
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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.
10 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
GPT-5 nano
OpenAI
2025-08-07
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Pricing Comparison
Cost per million tokens (USD)
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GPT-5 nano
Input:$0.05
Output:$0.40
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Llama 3.2 3B Instruct
Input:$0.01
Output:$0.02($0.42 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-5 nano
Average Score:71.2%(+38.4%)
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Llama 3.2 3B Instruct
Average Score:32.8%
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
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-5 nano
2 providers
OpenAI
Throughput: 500 tok/s
Latency: 0.3ms
ZeroEval
Throughput: 500 tok/s
Latency: 0.3ms
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GPT-5 nano
Avg Score:71.2%(+38.4%)
Providers:2
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Llama 3.2 3B Instruct
Avg Score:32.8%
Providers:1