On the 28th, Zhao Zhiyun, director of the Institute of Scientific and Technical Information of China, released the Research Report on the Map of China's Artificial Intelligence Big Model at the Zhongguancun Forum Parallel Forum "Artificial Intelligence Big Model Development Forum" held in Beijing. The report shows that China's big model is showing a thriving development trend. In recent years, China's large model technology has developed rapidly along various technical routes, and many large pre training models with industry influence have emerged in the fields of natural language processing, machine vision and multimodality. On site of the Zhongguancun Forum parallel forum "Artificial Intelligence Big Model Development Forum". At the forum, Zhao Zhiyun explained that various technological routes of China's big models are breaking through in parallel, especially in areas such as natural language understanding, machine vision, and multimodality, where multiple influential big models have emerged in the industry. According to incomplete statistics, so far, 79 large-scale models with parameters above 1 billion level have been released in China. The report points out that the geographical and domain distribution of China's large model is relatively concentrated. From the perspective of regional distribution, 14 provinces are conducting large-scale model research and development, mainly concentrated in Beijing and Guangdong. Among them, Beijing has 38 large-scale models and Guangdong has 20 large-scale models. From the perspective of field distribution, natural language processing is still the most active key field in research and development of large models, followed by multimodal field, and there are few large models in computer vision, intelligent voice and other fields. From the distribution of research and development entities, different innovation entities such as universities, research institutions, and enterprises are actively participating in large-scale model research and development, but there is still insufficient joint research and development between academia and industry. The report shows that Beijing, Guangdong, Zhejiang, Shanghai and other places have the highest number of large models; At the same time, these four places are also the regions with the highest number of artificial intelligence server purchases in the past three years. It is worth noting that Beijing, Jiangsu, Guangdong, Shanghai, and other regions have a relatively large number of large model talents, providing key intellectual support for the research and development of large models. On the other hand, large models have a high threshold and require high-quality AI talents. Currently, the number of large model talents in various regions is insufficient. In addition, in terms of academic influence, Beijing, Guangdong, and Shanghai all have the highest number of paper publications and citations in China. The report points out that China's large model research and development team is actively promoting the development of open source for large models, and currently more than half of the large models have achieved open source development. Beijing, Guangdong, and Shanghai all rank among the top three in terms of open source quantity and influence in China. Among them, universities and research institutions are the main force of open source. In response to the current development situation of large models in China, the report proposes four suggestions and prospects: firstly, strengthen the coordination of resources and research and development forces to promote the orderly development of large models. Strengthen the coordination of computing resources such as intelligent computing centers, supercomputing centers, and cloud computing centers, develop public data sharing directories and rules, and promote the orderly opening of data classification and classification. The second is to accelerate basic research and technological innovation, and enhance academic and open-source influence. The technology of large models is still in its early stages of development, with huge potential for basic theories and technological innovation. Through miniaturization technologies such as distillation and quantification, the model is "slimmed down", providing technical support for the miniaturization and green development of large models. At the same time, further strengthen cooperation between industry, academia, and research, and encourage open source of large models