An efficient MPI/OpenMP hybrid parallel Radial Basis Function (RBF) strategy for both continuous and discontinuous large-scale mesh deformation is proposed to reduce the compu-tational cost and memory consumption. Unlike the conventional parallel methods in which all pro-cessors use the same surface displacement and implement the same operation, the present method employs different surface points sets and influence radius for each volume point movement, accom-panied with efficient geometry searching strategy. The deformed surface points, also called Control Points (CPs), are stored in each processor. The displacement of spatial points is interpolated by using only 20–50 nearest control points, and the local influence radius is set to 5–20 times the max-imum displacement of control points. To shorten the searching time for the nearest control point clouds, an Altating Digital Tree (ADT) algorithm for 3D complex geometry is designed based on an iterative bisection technique. Besides, an MPI/OpenMP hybrid parallel approach is developed to reduce the memory cost in each High-Performance Computing (HPC) node for large-scale appli-cations. Three 3D cases, including the ONERA-M6 wing and a commercial transport airplane stan-dard model with up to 2.5 billion hybrid elements, are used to test the present mesh deformation method. The robustness and high parallel efficiency are demonstrated by a wing deflection case with a maximum bending angle of 45° and more than 80％parallel efficiency with 1024 MPI processors.In addition, the availability for both continuous and discontinuous surface deformation is verified by interpolating the projecting displacement with opposite directions surface points to the spatial points.