DeepSeek VL2 Small
Multimodal
Zero-eval
#2MMBench-V1.1
#2MME
#3MMT-Bench
by DeepSeek
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About
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%), TextVQA (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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Timeline
AnnouncedDec 13, 2024
ReleasedDec 13, 2024
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Specifications
Capabilities
Multimodal
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License & Family
License
deepseek
Performance Overview
Performance metrics and category breakdown
Overall Performance
14 benchmarks
Average Score
69.6%
Best Score
92.3%
High Performers (80%+)
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All Benchmark Results for DeepSeek VL2 Small
Complete list of benchmark scores with detailed information
| DocVQA | multimodal | 0.92 | 92.3% | Self-reported | |
| ChartQA | multimodal | 0.84 | 84.5% | Self-reported | |
| TextVQA | multimodal | 0.83 | 83.4% | Self-reported | |
| OCRBench | multimodal | 0.83 | 83.4% | Self-reported | |
| MMBench | multimodal | 0.80 | 80.3% | Self-reported | |
| AI2D | multimodal | 0.80 | 80.0% | Self-reported | |
| MMBench-V1.1 | multimodal | 0.79 | 79.3% | Self-reported | |
| InfoVQA | multimodal | 0.76 | 75.8% | Self-reported | |
| RealWorldQA | multimodal | 0.65 | 65.4% | Self-reported | |
| MMT-Bench | multimodal | 0.63 | 62.9% | Self-reported |
Showing 1 to 10 of 14 benchmarks