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DeepSeek VL2 Small vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Small leads with 3.2% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek VL2 Small is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 69.6% across 14 benchmarks. It excels particularly in DocVQA (92.3%), ChartQA (84.5%), OCRBench (83.4%). 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-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 2025, it represents OpenAI's latest advancement in AI technology.
4 months newer
DeepSeek VL2 Small
DeepSeek
2024-12-13
GPT-4.1 nano
OpenAI
2025-04-14
Performance Metrics
Context window and performance specifications
Average performance across 37 common benchmarks
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DeepSeek VL2 Small
Average Score:26.3%(+3.2%)
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GPT-4.1 nano
Average Score:23.1%
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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 VL2 Small
0 providers
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GPT-4.1 nano
1 providers
OpenAI
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DeepSeek VL2 Small
Avg Score:26.3%(+3.2%)
Providers:0
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GPT-4.1 nano
Avg Score:23.1%
Providers:1