As seen, all ML models improve raw xTB-sTDA values, but to different extents depending on the training and test set considered. For the MOPSSAM and PCQC-AL datasets, using larger datasets with more input data generally improves results. This result is intuitive, as more data allows the ML model to learn more about patterns in the datasets. The lowest MAE obtained was 0.08 eV using the Class 2 xTB-ML-300k model on T 1 energies of MOPSSAM 143.