To further test the models, we compared the direct ML model with 26 anions in the Minnesota Solvation Database 53 (MNSol/nonoverlap) along with previous COSMO-RS calcula-tions at the BP-TZVPD-FINE level and and cluster-continuum calculations. We aligned the proton solvation free energies to allow for fair comparison, and adjusted the experimental ∆G * solv (A -) values by -1.2 for the MNSol/overlap data because their gas-phase acidities came from NIST. In methanol, the direct ML model performs about as well if not slightly better than the other methods. The solutes in this set are all simple organic acids' conjugate anions, similar to the solutes that appear in the data used to train the model. In the other solvents, the ML model overall does not perform well. Individual predictions tend to be either very accurate (successful interpolation) or very inaccurate (high errors from extrapolation). For instance, in water, two of the lowest errors are from the direct ML model, but several outliers are also present including one that exceeds 12 kcal mol -1 , showing the variability of the model depending on provided inputs. The solutes with high errors tend to be exceptional compounds -such as the anion conjugates of chloroform, water, and DMSO.