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DeepSeek-V3 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 25.3% higher average benchmark score. GPT-4.1 nano offers 818.2K more tokens in context window than DeepSeek-V3. GPT-4.1 nano is $0.87 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, DeepSeek-V3 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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.
3 months newer
DeepSeek-V3
DeepSeek
2024-12-25
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3
Input:$0.27
Output:$1.10
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GPT-4.1 nano
Input:$0.10
Output:$0.40($0.87 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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DeepSeek-V3
Average Score:67.0%(+25.3%)
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GPT-4.1 nano
Average Score:41.7%
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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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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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GPT-4.1 nano
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DeepSeek-V3
Avg Score:67.0%(+25.3%)
Providers:1
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GPT-4.1 nano
Avg Score:41.7%
Providers:1