Tree tensor network states (TTNSs) combined with the density matrix renormalization group (DMRG) are emerging as powerful tools for vibrational and vibronic structure simulations in molecules with strong coupling and fluxionality. In this talk, I discuss how TTNS methods enable accurate, full-dimensional computations of thousands of eigenstates for molecular systems ranging from quartic-force-field benchmarks to molecules with strong vibronic coupling and protonated water clusters as large as the 33-dimensional Eigen ion, \(\mathrm{H_3O^+ \cdot (H_2O)_3}\). I will show that for a widely used benchmark system, DMRG algorithms can boost the number of computed states by a factor of five compared to other methods, while simultaneously increasing the accuracy by two orders of magnitude. Finally, I will show how to directly target excited eigenstates for these systems.