This article explores the performance of MCTDH, ML-MCTDH, AIMS, and decoherencecorrected fewest-switches surface hopping (DC-FSSH) dynamics when facing a long-timescale nonadiabatic molecular problem. These methods were selected because they are all well-established and represent diverse strategies of nonadiabatic simulations. Among these approaches, DC-FSSH is unambiguously the widespread methodology. It employs a swarm of classical independent trajectories propagating on a single potential energy surface (PES), each stochastically hops between electronic states, as a proxy for the nonadiabatic nuclear wavepacket. The hoppings are controlled by transition probabilities between states estimated from a local approximation of the time-dependent electronic Schrödinger equation (TDSE) corrected for overcoherence effects. On the other hand, MCTDH is a grid-based quantum dynamics approach for solving the timedependent Schrӧdinger equation (TDSE) and, thereby, is the most accurate. MCTDH, however, demands much computation power to describe the quantum nuclear motion on multiple coupled electronic states. In the ML-MCTDH formulation, the multidimensional time-dependent singleparticle functions (SPFs) generated from many mode combinations are propagated by MCTDH equations of motion, and it is carried out recursively for different layers of the ML tree.