To test QTAIM performance on predicting reaction-level properties we benchmarked a dataset recently published by Green et. al. This dataset consists of 12, 000 reactions with barrier heights and reaction enthalpies computed at three levels of theory. Reactions in the dataset involve only C, N, O, and/or H atoms with up to 7 heavy atoms. We benchmarked predicting activation energies at the highest level of theory they were computed (CCSD(T)-F12a 46 /def2-TZVP ). We constructed a random train-test split of 90/10 and the validation set was constructed from the training set with a random split of 80/20 for model selection and hyperparameter tuning. QTAIM here was computed at TPSS 33 /def2-SVP with D3BJ dispersion level of theory given the large number of individual molecules in the entire dataset.