The QM9 and rMD17 datasets are used to benchmark the predictive performance of small molecules. The QM9 dataset contains around 134k small organic molecules with electronic, energetic, and thermodynamic properties computed with the B3LYP functional. We have used the purified version of QM9 where 30,054 molecular structures were excluded from training and evaluation because of inconsistency. It is found that PiNet2-P3 achieves a MAE of 8.0 ± 0.1 meV in predicting internal energy at 0K, compared to 12 meV MAE of the original PiNet for the same data splitting.