China is undergoing rapid urbanization, which brings about drastic land cover changes and thus has an important impact on land carbon stocks. Therefore, it is of great significance to study the driving factors of land cover changes in typical cities and simulate their carbon stocks in multiple scenarios, in order to promote the development of sustainable use of land resources and to achieve the goal of “dual-carbon.” In this study, based on the synergistic relationship between land cover and carbon stock (CS), a coupled modeling framework based on MOP-FLUS-InVEST (MFI) is proposed, which integrates the advantages of three models: targeted optimization of the land cover (LC) structure, patch-level simulation of the layout, and rapid probing of spatial and temporal evolutions of CS. In addition, based on the 30 m resolution surface cover data, we analyzed the land cover change characteristics of Shijiazhuang, a city undergoing rapid urbanization in China, from 2000 to 2020 using a dynamic attitude model. The results show that the rate of surface cover change in Shijiazhuang City is relatively fast, but the rate of surface cover change gradually slows down during the 20-year period. The LC change is mainly manifested in the mutual transfer of cropland, woodland and grassland. In the future, the area of cropland, water bodies and bare land decreases, the business-as-usual development (BAU) scenario has the most drastic increase in construction land, and the changes in woodland and grassland are weak, with an increase in economic benefits. In the Ecological Priority Development (EDP) scenario, woodland and grassland expand significantly while construction land growth stagnates, and ecological functions are restored. In the Ecologically and Economically Balanced Development (EEB) scenario, ecological land increases and the growth of built-up land slows down, realizing both economic and ecological benefits. The continuous shrinkage of water bodies is a pressing issue. The coupled model can provide scientific references for the simulation of spatial and temporal changes of LC and CS, the early warning of ecological risks, and the development of land cover planning.