DeepSeek VL2 Tiny
Multimodal
Zero-eval
#3MME
by DeepSeek
+
+
+
+
About
DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). 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.
+
+
+
+
Timeline
AnnouncedDec 13, 2024
ReleasedDec 13, 2024
+
+
+
+
Specifications
Capabilities
Multimodal
+
+
+
+
License & Family
License
deepseek
Performance Overview
Performance metrics and category breakdown
Overall Performance
14 benchmarks
Average Score
63.1%
Best Score
88.9%
High Performers (80%+)
4+
+
+
+
All Benchmark Results for DeepSeek VL2 Tiny
Complete list of benchmark scores with detailed information
| DocVQA | multimodal | 0.89 | 88.9% | Self-reported | |
| ChartQA | multimodal | 0.81 | 81.0% | Self-reported | |
| OCRBench | multimodal | 0.81 | 80.9% | Self-reported | |
| TextVQA | multimodal | 0.81 | 80.7% | Self-reported | |
| AI2D | multimodal | 0.72 | 71.6% | Self-reported | |
| MMBench | multimodal | 0.69 | 69.2% | Self-reported | |
| MMBench-V1.1 | multimodal | 0.68 | 68.3% | Self-reported | |
| InfoVQA | multimodal | 0.66 | 66.1% | Self-reported | |
| RealWorldQA | multimodal | 0.64 | 64.2% | Self-reported | |
| MathVista | multimodal | 0.54 | 53.6% | Self-reported |
Showing 1 to 10 of 14 benchmarks