The modest computational costs of CSS-AIMS and DC-FSSH are associated with the analytical model used to provide information on electronic structure. Usually, these methods work with an onthe-fly approach, invoking a third-party program to solve the electronic problem for the specific nuclear geometry. If that were the case, the computational costs would likely blow up unless low-cost parameterized methods or machine learning potentials were used. Naturally, the comparison would also have to account for the price of building the potential energy surfaces used in MCTDH and ML-MCTDH.