A recently released research report by Carnegie Mellon University (CMU) conducted an in-depth comparative analysis of Google Gemini Pro and OpenAI GPT-3.5. The research covers multiple fields such as knowledge question answering and general reasoning, and evaluates the performance difference between the two models through multi-task testing. The report results show that although Gemini Pro has advantages in some aspects as a multi-modal model, GPT-3.5 still shows stronger performance in most tests, especially in knowledge question and answer and general reasoning.
Webmaster Home reported that CMU research showed that there is not much difference between Gemini Pro and GPT-3.5, but it is slightly insufficient in multi-task tests. Research covers many fields, and GPT-3.5 leads the way in knowledge question answering and general reasoning. Although Gemini Pro is a multi-modal model, GPT-3.5 maintains excellent performance in most tests.
All in all, this research by CMU provides a valuable reference for us to have an in-depth understanding of the performance differences between Gemini Pro and GPT-3.5, and also provides new inspiration for the development direction of large-scale language models in the future. Although Gemini Pro has made some attempts in multi-modality, GPT-3.5 still has obvious advantages in core capabilities. Follow-up research may focus on how to better combine multi-modal capabilities with powerful reasoning capabilities.