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DeepSeek-V3.1 vs GPT-5 nano
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 16.6% higher average benchmark score. GPT-5 nano offers 200.3K more tokens in context window than DeepSeek-V3.1. GPT-5 nano is $0.82 cheaper per million tokens. GPT-5 nano supports multimodal inputs. Overall, GPT-5 nano 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-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.
6 months newer
DeepSeek-V3.1
DeepSeek
2025-01-10
GPT-5 nano
OpenAI
2025-08-07
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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-5 nano
Input:$0.05
Output:$0.40($0.82 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek-V3.1
Average Score:43.5%
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GPT-5 nano
Average Score:60.2%(+16.6%)
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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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DeepSeek-V3.1
2 providers
DeepInfra
Novita
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GPT-5 nano
2 providers
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DeepSeek-V3.1
Avg Score:43.5%
Providers:2
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GPT-5 nano
Avg Score:60.2%(+16.6%)
Providers:2