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DeepSeek VL2 vs GPT-5 nano
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 39.1% higher average benchmark score. GPT-5 nano offers 269.4K more tokens in context window than DeepSeek VL2. GPT-5 nano is $4809.05 cheaper per million tokens. Overall, DeepSeek VL2 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek VL2 is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 70.9% across 14 benchmarks. It excels particularly in DocVQA (93.3%), ChartQA (86.0%), TextVQA (84.2%). It supports a 259K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
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OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
7 months newer
DeepSeek VL2
DeepSeek
2024-12-13
GPT-5 nano
OpenAI
2025-08-07
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek VL2
Input:$9.50
Output:$4800.00
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GPT-5 nano
Input:$0.05
Output:$0.40($4809.05 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 19 common benchmarks
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DeepSeek VL2
Average Score:52.2%(+39.1%)
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GPT-5 nano
Average Score:13.2%
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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 VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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GPT-5 nano
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DeepSeek VL2
Avg Score:52.2%(+39.1%)
Providers:1
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GPT-5 nano
Avg Score:13.2%
Providers:2