a large dataset to a small, more expensive one is a very powerful idea which has gained some popularity in the field of MLFF. Multiple large, and mutually incompatible datasets of druglike molecules have already appeared in the literature. The very popular QM9 dataset consists of various properties of 134,000 organic molecules computed at the B3LYP/6-31G(d, p) level, the ANI dataset consists of 20 million examples computed at the ωB97X/6-31G(d) level, the ANI-1x dataset consists of roughly 5 million examples labeled with the ωB97X functional with both the 6-31G(d) and def2-TZVPP basis sets whereas the ANI1-CCX dataset is 500,000 examples labeled with DLPNO-CCSD(T)/CBS. The OrbNet Denali dataset consists of roughly 2 million examples labeled at the ωB97X-D3/def2-TZVP level, and finally the SPICE dataset was reported with 1.1 million examples at the ωB97M-D3(BJ)/def2-TZVPPD level. None of these datasets can be naively combined since they represent different model chemistries.