Concerning computational efficiency, we note that, compared with the Einstein Crystal method (ECM), the PGM approach requires performing only two simulations of the physical end-states of interest vs. simulations in all the overlapping intermediate perturbed Hamiltonians necessary to converge the ECM method. Taking into account these aspects and considering the total number of configurations generated by MD necessary to converge the lattice-free energy differences as a figure of merit to assess efficiency, we note that the reweighted-PGM methods require only ≈17% of the configurations needed by the ECM, leading to an increase in efficiency of FE of factor between 5 and 6. We anticipate that such an efficiency gain will increase when considering more complex molecular systems. We further note that the computational overheads associated with training PGMs by maximum likelihood are agnostic to the quality and computational cost of the potential energy functions used to sample the training data. This opens up future possibilities of computing fully anharmonic free energy differences, remapped to forcefields at a higher level of theory. The choice of a common base distribution, the application to FE differences in a wide and practically relevant range of temperatures, the flexible representation of individual molecules, and the application to packing polymorphs with nonoverlapping high-temperature distributions provide a step forward with respect to the literature on PGM-based FE calculations on molecular crystals. As such, these results represent a stepping stone towards adopting normalizing flow methods into the anharmonic FE toolbox of practitioners dealing with finite temperature ranking of large sets of molecular crystalline solids. More broadly, when taken together with several key recent developments in this field , we can further expect normalizing flows to begin solving increasingly diverse real-world problems in the foreseeable future.