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GPT-4.1 nano vs Llama 3.1 Nemotron 70B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. GPT-4.1 nano supports multimodal inputs. 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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NVIDIA
Llama 3.1 Nemotron 70B was developed by NVIDIA through customization of Meta's Llama 3.1 70B, designed to enhance performance for specific use cases and deployments. Built with NVIDIA's optimizations and fine-tuning expertise, it demonstrates how foundation models can be adapted for specialized applications.
6 months newer
Llama 3.1 Nemotron 70B Instruct
NVIDIA
2024-10-01
GPT-4.1 nano
OpenAI
2025-04-14
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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GPT-4.1 nano
Average Score:80.1%
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Llama 3.1 Nemotron 70B Instruct
Average Score:80.2%(+0.1%)
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Knowledge Cutoff
Training data recency comparison
Llama 3.1 Nemotron 70B Instruct
2023-12-01
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 3.1 Nemotron 70B Instruct
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GPT-4.1 nano
Avg Score:80.1%
Providers:1
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Llama 3.1 Nemotron 70B Instruct
Avg Score:80.2%(+0.1%)
Providers:0