Simulation performance is the main factor that limits the broad applications of QM/MM MD, whereas ML/MM MD provides a promising alternative. Therefore, for further ML/MM MD development, performance is a primary concern. We collected data from protein-ligand systems to evaluate the effectiveness of our built-in methods and parallel processing approaches in accelerating computations. All computation results were obtained using the NVIDIA L40s and the Intel Xeon Platinum 8462Y+. Figures and illustrate the performance of the ANI-2x and MACE-OFF23(S) models within the ML/MM framework. In most cases using ANI-2x, simulations achieve over 2 ns/day, while MACE operates at approximately 1.5 ns/day. Notably, all simulations used a timestep of 1 fs. When bonds involving hydrogen were constrained using the SHAKE algorithm, the timestep can be extended to 2 fs. This approach is suitable for large systems where detailed hydrogen behavior is not the focus, effectively doubling the simulation performance.