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DeepSeek-V3.2-Exp vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 47.2% higher average benchmark score. GPT-4.1 nano offers 851.0K more tokens in context window than DeepSeek-V3.2-Exp. Both models have similar pricing. GPT-4.1 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-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.
5 months newer
GPT-4.1 nano
OpenAI
2025-04-14
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-4.1 nano
Input:$0.10
Output:$0.40($0.18 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:77.2%(+47.2%)
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GPT-4.1 nano
Average Score:30.0%
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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-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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GPT-4.1 nano
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DeepSeek-V3.2-Exp
Avg Score:77.2%(+47.2%)
Providers:2
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GPT-4.1 nano
Avg Score:30.0%
Providers:1