In contrast to the overall decent performance of DFT and wavefunction methods, semiempirical methods performed poorly on Wiggle150. We studied 4 semiempirical methods: Grimme and coworkers' extended tight binding methods, GFN1-xTB and GFN2-xTB, and the older methods AM1 and PM3. In terms of both MAE and RMSE, newer methods are worse than older methods: GFN2-xTB < GFN1 < PM3 < AM1. While accuracy on single-point-energy benchmarks is not a primary objective of the xTB methods, these data suggest that the additional complexity of newer semiempirical methods may lead to unreliable performance on strained structures very different from the structures these methods were optimized on. Future generations of xTB methods incorporating additional physics, like approximate non-local Fock exchange, may be able to address these shortcomings. The two forcefields studied here both gave dismal results. The failure of Sage, a conventional forcefield similar to the Amber forcefields, is unsurprising: 2017 study by Kanal and co-workers argued that commonly used forcefields "should not be trusted" for conformer ranking, and that their predictions are "wholly unreliable for conformer screening." In contrast, the poor performance of GFN-FF is more unexpected: in their initial publication describing GFN-FF, Spicher and Grimme report that GFN-FF is "on par with some dispersion-corrected DFT methods" at describing relative conformer energies. Our results show that this is not true for the high-energy conformers studied here. The Pareto Frontier of Computational Methods. Many of the applications for which good performance on non-equilibrium structures is required, like automated reaction-path exploration and various molecular dynamics-based workflows, also require large numbers of calculations to be run. We compared the speed and accuracy of different methods, with the goal of identifying points along the Pareto frontier suitable for various use cases. The resulting plots of RMSE vs runtime are shown below (Figure ).