On September 5, 2022, a magnitude 6.8 earthquake occurred along the Xianshuihe Fault Zone in Luding County, Tibetan Plateau, China, leading to a significant outbreak of landslides. The urgent need for a swift and accurate evaluation of earthquake-induced landslides distribution in the affected area prompted this study. This research delves into regional geological data, scrutinizes post-earthquake Peak Ground Acceleration (PGA) and Arias Intensity (Ia) associated with the Luding earthquake, and conducts earthquake-induced landslides risk assessments within the Luding earthquake zone using the Newmark model. Validation of the earthquake-induced landslides risk assessment outcomes rooted in PGA and Ia relies on an earthquake-induced landslides database, revealing Area Under the Curve (AUC) values of 0.73 and 0.84 in respective ROC (Receiver Operating Characteristic) curves. These results unequivocally affirm the exceptional accuracy of earthquake-induced landslides evaluation using Ia calculations, emphasizing its suitability for the swift prediction and evaluation of earthquake-induced landslides. The earthquake-induced landslides risk assessment based on Ia computation reveals the area with extremely high-risk and high-risk of earthquake-induced landslides encompass 0.71% of the entire study area. Notably, these areas are predominantly clustered within seismic intensity VII zones and primarily trace the Moxi fault zone, extending from the southern portion of the middle east along the Dadu River and the Moxi fault, with reach up to Dewei Township in the north and Caoke Township in the south. Hazard-prone regions predominantly align with slopes featuring gradients of 30°–45° and bear a strong correlation with fault activity. Furthermore, the results of this evaluation are harmonious with the findings from remote sensing interpretation and on-site field investigations pertaining to the earthquake-induced landslides. This body of knowledge can serve as a crucial reference for expedited assessment, emergency response and subsequent supplementation of earthquake-induced landslide databases when confronting similar earthquake-induced landslide scenarios.