Abstract:[Objective] This study quantitatively analyzed the specific situation of the infrastructure carrying capacity of Chinese national central cities from 2006 to 2017 to provide a scientific basis for promoting the development of national central cities.[Methods] The panel data of the infrastructure carrying capacity of national central cities from 2006 to 2017 were selected to construct an evaluation index system of the urban infrastructure carrying capacity from two levels:pressure and state. The entropy TOPSIS method and obstacle degree model were used to evaluate and diagnose the infrastructure carrying capacity and its obstacle factors for national central cities from 2006 to 2017. In addition, the status of the infrastructure carrying capacity was quantitatively measured and the obstacle factors were diagnosed based on the evaluation results of the infrastructure carrying capacity.[Results] From 2006 to 2010, the level of the infrastructure carrying capacity in national central cities generally increased significantly, and the growth rate of the infrastructure carrying capacity slowed down from 2011 to 2017. Specifically, the infrastructure carrying capacity in Beijing, Shanghai, Chengdu, Zhengzhou, and Xi'an cities increased significantly, whereas that in Guangzhou City was the smallest. The infrastructure carrying capacity also continued to increase as the population of the cities increased. The analysis using the obstacle degree model revealed that the main factors restricting the infrastructure carrying capacity in the national central cities were the per capita green space area, the per capita annual household water consumption, and the urban mobile phone penetration rate.[Conclusion] With the development of China's economy, the siphoning effect of central cities on the population is becoming increasingly intense. The per capita green space area, urban mobile phone penetration rate, and per capita annual household water consumption might be decoupled from a city's economy and population size, which would not be able to meet the daily infrastructure needs of the population.