In this contribution, we aim to provide an in-depth exploration of the robustness of state-of-the-art GNN potentials based on the GemNet architecture 21 in MD simulations. To this end, we ran a total of 245 ns of dynamics (around 500 million timesteps) across a wide range of temperatures and organic molecules. By checking samples from these large ensembles with DFT reference calculations, the extrapolative capabilities of these potentials in configuration and chemical space was tested simultaneously. Furthermore, the impact of training set size on the robustness of the potentials was explored.