Despite the importance of soil as a large component of the terrestrial ecosystem, the soil compartments are not well represented in land surface models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the Institut Pierre Simon Laplace (IPSL) LSM called ORCHIDEE-SOM (ORganizing Carbon and Hydrology in Dynamic EcosystEms-Soil Organic Matter), incorporating the C-14 dynamics into the soil. ORCHIDEE-SOM first simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon and its transport are modelled. Finally, soil organic carbon decomposition is considered taking into account the priming effect. After implementing C-14 in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and modern C-14 fraction ((FC)-C-14) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the (FC)-C-14 along the vertical profiles for the sites examined. However, an overestimation of the total carbon stock was noted, primarily on the surface layer. Due to C-14, it is possible to probe carbon age in the soil, which was found to be underestimated. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations, whereas the second test improved both estimation of surface soil carbon stock as well as soil carbon age. This demonstrates that we should focus more on vertical variation in soil parameters as a function of depth, in order to upgrade the representation of the global carbon cycle in LSMs, thereby helping to improve predictions of the of soil organic carbon to environmental changes.