Current MLLMs show uneven and often poor understanding of scientific visualizations, particularly failing at quantitative tasks and complex visualization types, suggesting that SciVis literacy should be a core evaluation criterion for multimodal AI systems.
This paper evaluates six multimodal large language models (MLLMs) on their ability to understand scientific visualizations using a standardized 49-item assessment test.