The computation time of a single point (energy + gradient) calculation provides a rough approximation of the method's cost for a torsion scan or geometry optimization. When examining the OpenFF QM datasets of small molecules, it is observed that a geometry optimization typically requires a median of 42 gradient calculations (based on data from approximately 8000 geometry optimizations). Additionally, a 1D torsion scan with 24 grid points generally costs around 788 gradient calculations (from data on roughly 4000 torsion scans). As a rule of thumb, a geometry optimization calculation is 40x costlier than a single point energy and gradient calculation, and a 1D torsion scan is 800x costlier if executed serially, or nearly 72-fold for parallelized torsion scans (considering the median of maximum number of optimization steps taken among all grid points). So, the differences scale up pretty quickly with the type of calculation. To provide a reference point, we present timing data for a molecule containing 16 heavy atoms. The timings were normalized with the time for a B3LYP-D3(BJ)/DZVP calculation. The cost factor versus RMSE plot is shown in Figure , and the most accurate functional is almost twice the cost of a B3LYP-D3(BJ)/DZVP calculation, despite only a modest accuracy benefit. It is to be noted that Psi4, as of v1.4.1, does not yet have analytic gradients for NL and VV10 dispersion terms, and also for DSD-BLYP method, so for these methods only the costs of an energy calculation were reported and scaled with respect to the cost of a B3LYP-D3(BJ) energy calculation.