We conducted a benchmark of QM levels of theory that strike a balance between accuracy and computational efficiency for generating large QM datasets with diverse chemistries to train the valence parameters in a general small molecule force field. The benchmark set of molecules included charged molecules, biaryls, complex hypervalent sulfur chemistry, and complex nitrogen chemistry. This benchmark study is an extension to an earlier work 2 on benchmarking conformer energies, which suggested B3LYP-D3(BJ)/DZVP as the level of theory to generate OpenFF force field training and validation data. In the context of force field development, aside from conformer energies and optimized geometries, torsion energy profiles represent another indispensable source of molecular interaction data. Achieving accuracy in torsion profile energies relative to a highly accurate QM level of theory reflects in the trained force field. For this purpose, relative energies were compared against CCSD(T)/[haTQZ; δ:haDZ]//MP2/haTZ level of theory for different functional and basis set combinations. And, among the tested methods, ωB97M-D3(BJ) outperforms the others even within a smaller basis set of DZVP, boasting an RMSE in torsion profile energies of just 0.41 kcal/mol. This range-separated hybrid functional has consistently ranked among the top performers in various recent studies 43,44 which were done with a larger basis set.