Solid-state batteries have received increasing attention in scientific and industrial communities, which benefits from the intrinsically safe solid electrolytes (SEs). Although much effort has been devoted to designing SEs with high ionic conductivities, it is extremely difficult to fully understand the ionic diffusion mechanisms in SEs through conventional experimental and theoretical methods. Herein, the temperature-dependent concerted diffusion mechanism of ions in SEs is explored through machine-learning molecular dynamics, taking Li10GeP2S12 as a prototype. Weaker diffusion anisotropy, more disordered Li distributions, and shorter residence time are observed at a higher temperature. Arrhenius-type temperature dependence is maintained within a wide temperature range, which is attributed to the linear temperature dependence of jump frequencies of various concerted diffusion modes. These results provide a theoretical framework to understand the ionic diffusion mechanisms in SEs and deepen the understanding of the chemical origin of temperature-dependent concerted diffusions in SEs.