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GPT-5 nano vs Llama 3.1 70B Instruct
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 29.5% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than Llama 3.1 70B Instruct. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Llama 3.1 70B Instruct is available on 9 providers. 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 3.1 70B was created as a balanced open-source model, designed to provide strong performance with 70 billion parameters while remaining practical for many deployment scenarios. Built to serve as a versatile foundation for fine-tuning and application development, it combines capability with accessibility in the open-source ecosystem.
1 year newer
Llama 3.1 70B Instruct
Meta
2024-07-23
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 3.1 70B Instruct
Input:$0.20
Output:$0.20($0.05 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%(+29.5%)
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Llama 3.1 70B Instruct
Average Score:41.7%
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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%(+29.5%)
Providers:2
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Llama 3.1 70B Instruct
Avg Score:41.7%
Providers:9