The Solvation GNN and DirectML models show high predictive quality; however, their accuracy is likely overestimated due to significant overlap between training and test molecules. For example, the experimental training data of Solvation GNN and DirectML contain, respectively, 29 (34 for pretraining) and 35 of the 38 molecules of EXT-Zamora, and, respectively, 4 (7 for pretraining) and 14 of the 16 molecules of EXT-SAMPL9. In fact, we observe a similar accuracy of the Solvation GNN and DirectML on EXT-SAMPL9 compared to the multi-target D-MPNN, although some molecules are already included in training, thus indicating at most comparable generalization capabilities.