Large Model Review

A comprehensive evaluation tool for Chinese big models, which truly reflects the general ability of big models through a multi-dimensional and multi-perspective evaluation system, and helps technical progress and industrialization development.

An open-source big model capability assessment system designed to comprehensively and quantitatively assess the capabilities of big models in knowledge, language, understanding, reasoning, etc., and to drive iterative optimization of the models.

Initiated by Stanford University, it aims to comprehensively assess the capabilities of big language models through multiple dimensions and scenarios in order to drive technological advancement and model optimization of the evaluation benchmark.

A comprehensive, scientific, and fair big model evaluation system and open platform aims to help researchers assess the performance of basic models and training algorithms in an all-round way by providing multi-dimensional evaluation tools and methods.

It is a comprehensive assessment platform focusing on evaluating the general ability of large models in human cognition and problem solving tasks, which is jointly created by well-known universities and organizations, providing diversified assessment methods and authoritative rankings to help the development and application of AI technology.