In this paper, we evaluate different abilities of GPT-4V including visual
understanding, language understanding, visual puzzle solving, and understanding
of other modalities such as depth, thermal, video, and audio. To estimate
GPT-4V's performance, we manually construct 656 test instances and carefully
evaluate the results of GPT-4V. The highlights of our findings are as follows:
(1) GPT-4V exhibits impressive performance on English visual-centric benchmarks
but fails to recognize simple Chinese texts in the images; (2) GPT-4V shows
inconsistent refusal behavior when answering questions related to sensitive
traits such as gender, race, and age; (3) GPT-4V obtains worse results than
GPT-4 (API) on language understanding tasks including general language
understanding benchmarks and visual commonsense knowledge evaluation
benchmarks; (4) Few-shot prompting can improve GPT-4V's performance on both
visual understanding and language understanding; (5) GPT-4V struggles to find
the nuances between two similar images and solve the easy math picture puzzles;
(6) GPT-4V shows non-trivial performance on the tasks of similar modalities to
image, such as video and thermal. Our experimental results reveal the ability
and limitations of GPT-4V and we hope our paper can provide some insights into
the application and research of GPT-4V.

GPT-4V 的能力和限制在视觉理解、语言理解、视觉拼图解决以及其他模态（如深度、热力、视频和音频）方面被评估，发现其在英语视觉基准上表现出色，但无法识别图像中的简单中文文本；在敏感特征问题、语言理解任务和类似图片之间差异的解决方面存在一些不一致性和限制，但通过少样本提示可以提高其性能；此外，在视频和热力等与图像类似的任务上表现出了非常好的性能。