Rivers connect the terrestrial landscape and oceans and are considered “bioreactors” of carbon. Understanding the carbon cycling processes in rivers and constructing numerical models for riverine carbon cycling is imperative to estimate regional and global carbon budgets. The summary and discussion of the development and application of riverine carbon cycling models remains inadequate. This study reviewed the mechanisms and models of riverine carbon cycling based on a comprehensive literature review. First, we briefly overview the critical processes in migrating and transforming various carbon components, including particulate organic carbon, dissolved inorganic carbon, and dissolved organic carbon. Riverine carbon cycling models are classified into two types: statistical and process-based. The representative models’ simulation methods, applications, advantages, and disadvantages were compared. Based on statistical or machine learning methods, empirical statistical models establish the relationship between the riverine carbon flux and environmental factors. This type of model is simple but has poor extrapolation and universality. Process-based models are based on land surface or hydrological models coupled with river carbon cycling-related biogeochemical processes. This model simulates and predicts variations in different riverine carbon fluxes and is more reliable but complicated. Such models typically focus on different scientific problems, and the representations of riverine carbon cycling-related processes differ among these models. Simulation research on riverine carbon cycling is still in its early stages; however, many shortcomings remain. For example, the representations of terrestrial and aquatic carbon cycling and human activities in existing riverine carbon cycling models are insufficient; thus, they cannot accurately simulate and predict long-term changes in riverine carbon cycling. In the future, it will be necessary to strengthen observations of river carbon cycling processes and improve our understanding of terrestrial and aquatic carbon cycling to represent the mechanisms and processes in the model. This will improve the accuracy of riverine carbon cycling simulations and provide a scientific basis for China to achieve its double-carbon goals.