solute errors ranging from 0.02 to 0.17 e -, which exceed the statistical error measures for the chemically more meaningful, randomly selected molecules but remain within a comparable range. This underscores the value of using a chemically diverse training set to improve the method's robustness. The trend observed in Fig. is further supported by the statistical comparison of 100 distinct MLMs in Fig. (technical details are given in the SI). In addition to the EEQ model, we compared the results with GFN2-xTB. The CEH-v2 model produces significantly fewer data points with large deviations from the 1:1 line than both EEQ and GFN2-xTB. This is reflected in the correlation measures with respect to the reference charges listed in