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DeepSeek-V3.1 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
DeepSeek-V3.1 leads with 40.0% higher average benchmark score. GPT-4.1 nano offers 752.7K more tokens in context window than DeepSeek-V3.1. GPT-4.1 nano is $0.77 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, DeepSeek-V3.1 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.1 was developed as an incremental advancement over DeepSeek-V3, designed to refine the mixture-of-experts architecture with improved training techniques. Built to enhance quality and efficiency while maintaining the open-source philosophy, it represents continued iteration on DeepSeek's flagship model line.
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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-V3.1
DeepSeek
2025-01-10
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.00
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GPT-4.1 nano
Input:$0.10
Output:$0.40($0.77 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-V3.1
Average Score:69.9%(+40.0%)
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GPT-4.1 nano
Average Score:29.8%
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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
2 providers
DeepInfra
Novita
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GPT-4.1 nano
1 providers
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DeepSeek-V3.1
Avg Score:69.9%(+40.0%)
Providers:2
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GPT-4.1 nano
Avg Score:29.8%
Providers:1