Levenberg–Marquardt or Adam optimization

In RBF (radial basis functions)-Neural Networks, which method (Levenberg–Marquardt or Adam optimization) is more efficient for optimizing the parameters (centers, widths, and output weights) in PyTorch? why?
In what condition Levenberg–Marquardt works better?