Abstract: With the emergence of ChatGPT,large model have become a new track for global technology competition,and have begun to be widely used in all aspects of production and life.Many domestic technology companies have invested in large model research and development and open source work.As the application scenarios of large model continue to expand,there are more and more types and quantities of pre-trained large model that can be downloaded or invoked,and users’ demand for large model eva-luation is gradually increasing.At present,there is no standardized method for the evaluation of large model,and the industry mainly compares the capability of large models through the evaluation lists provided by third-party institutions.There is still a lack of effective measurement methods for the actual effect of large models in specific application scenarios.In this paper,a cross evaluation method is proposed to evaluate the application effect of the pre-trained large model in the vertical industry scenario,especially the answering ability of open questions,and its reliability and robustness are verified by experiments.The cross-evaluation method proposed in this paper has a high consistency with the official results,indicating that the method has a strong reliability.This method effectively improves the objectivity and convenience of large model evaluation,and helps users to quickly complete the horizontal comparison and selection of large models in personalized scenes.

Key words: Evaluation method, Cross evaluation, Open-ended question, Candidate large model, Judge large model