In this work we consider four flavors of NFFs: SchNet , PaiNN , Allegro , and SpookyNet . This series of models represents increasingly physics-informed model architectures, from models with internal layers that manipulate only E(3) invariant quantities (SchNet) to those that use E(3) equivariant quantities (PaiNN, Allegro, SpookyNet), strictly local models with learned many-body functions and no message passing (Allegro), and physically-informed via empirical corrections (SpookyNet). The power and expressivity of these GNNs can be defined in terms of their capacity ,