Our investigation of Vendi sampling in several challenging systems reveals its ability to rapidly detect free energy minima, particularly in cases where there are large free energy barriers between states. Moreover, Vendi sampling enables the rapid convergence to the unbiased equilibrium statistics, facilitating the computation of observables such as free energy differences. We accomplished these findings using generic kernels, which do not encode slowly relaxing degrees of freedom. However, the current implementation incurs some computational overhead. We anticipate that further research into the development of more efficient kernels and the use of multiple time-stepping schemes can further boost the performance of Vendi sampling.