The nascent research field of nonadiabatic dynamics in the long timescale has focused on computational cost reduction through parameterized methods, dimensionality reductions, strong approximations, ergodic extensions, and machine-learning models. Nevertheless, proper nonadiabatic dynamics in the long timescale must also deal with other issues beyond costs, such as integration stability and error accumulation. Indeed, it is altogether unclear if the results of the most currently used nonadiabatic methodologies even make sense in the long timescale. For instance, does the fewest-switches approximation employed in trajectory surface hopping hold under the weak couplings experienced in long timescales? Is the time-dependent Hartree expansion in MCTDH robust enough to be integrated for tens of picoseconds? Unambiguously, the literature predominantly compares nonadiabatic dynamics methods within the ultrafast timescales. Despite several comparisons between quantum dynamics and mixed quantum-classical dynamics methods involving FSSH, AIMS, and MCTDH, an important question remains: How well do the nonadiabatic dynamics methods behave at a long timescale?