The General Language Understanding Evaluation (GLUE) benchmark is widely used to evaluate Natural Language Processing (NLP) models. Although GLUE includes a range of English sentence-pairing, word prediction and other NLP tasks, it cannot evaluate the performance of Chinese NLP models. Now, a group of NLP researchers and enthusiasts, including graduates from Tsinghua University, Peking University, and Zhejiang University, have introduced ChineseGLUE, a benchmark designed to encourage the development and assessment of Chinese language models. GLUE was introduced in 2018 by researchers from New York University, University of Washington and DeepMind. Since then, new pretrained language models such as Google's BERT have rapidly improved performance in Natural Language Understanding (NLU), a NLP research area with a focus on machine reading comprehension through sentiment analysis and grammatical judgment, etc.