The best finetuned model for each foundational model was trained using 6000 structures sampled by average zinc coordination number. The error for these models is summarized in Figure which shows MACE-MP-0 outperformed SevenNet-0, however both demonstrate To illustrate the ability of these models to correctly predict coordination environments as the structure evolves at high temperature, the 15 ps DFT trajectories were for CALF-20 and ZIF-8 were recreated. The MACE "from scratch" model trained using coordination number sampling was employed using the same 0.5 fs timestep and ensemble details to match the DFT trajectories. For each DFT and MLP dataset, RDFs were generated using the equilibrated region (Figure ). These RDFs show a maximum difference of 5.13 % between MLP and DFT trajectories for ZIF-8 at 2000 K and 4.12 % for CALF-20 at 2000 K. This reinforces that the MLP successfully captures the behavior of CALF-20 and ZIF-8 at these temperatures. There is less deviation for CALF-20 than ZIF-8 despite the energy, force and stress being represented with less error for ZIF-8 (Supplementary Tables ). This suggests that energy, force and stress are reaching an accuracy such that the MLP can correctly predict the behavior of both MOFs at these high temperatures.