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DeepSeek-V2.5 vs GPT-5 nano
Comprehensive side-by-side LLM comparison
GPT-5 nano offers 511.6K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation 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.
1 year newer
DeepSeek-V2.5
DeepSeek
2024-05-08
GPT-5 nano
OpenAI
2025-08-07
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($0.03 cheaper)
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GPT-5 nano
Input:$0.05
Output:$0.40
Performance Metrics
Context window and performance specifications
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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-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:0.0%
Providers:3
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GPT-5 nano
Avg Score:0.0%
Providers:2