We focused on assessing the impact of the ML region size on computational efficiency, the ability of the Torch-accelerated ML/MM implementation to utilize GPU resources effectively, and whether the MM region represents a bottleneck. To evaluate these aspects, we ran simulations of a capped alanine octapeptide in aqueous solution, incrementally increasing the number of residues included in the ML region. Our scheme can take full advantage of the MPI capabilities of sander, so we also benchmarked the scaling with respect to CPU cores in this regard.