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DeepSeek-V3.2-Exp vs GPT-5 nano
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 8.0% higher average benchmark score. GPT-5 nano offers 298.6K more tokens in context window than DeepSeek-V3.2-Exp. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Overall, DeepSeek-V3.2-Exp is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.2-Exp was introduced as an experimental release, designed to test new architectural innovations and training methodologies. Built to explore the boundaries of mixture-of-experts design, it serves as a research preview for techniques that may be incorporated into future stable releases.
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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 month newer
GPT-5 nano
OpenAI
2025-08-07
DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2-Exp
Input:$0.27
Output:$0.41
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GPT-5 nano
Input:$0.05
Output:$0.40($0.23 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:68.2%(+8.0%)
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GPT-5 nano
Average Score:60.2%
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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-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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GPT-5 nano
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DeepSeek-V3.2-Exp
Avg Score:68.2%(+8.0%)
Providers:2
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GPT-5 nano
Avg Score:60.2%
Providers:2