Nevergrad seems more similar to Nelder Mead optimization, except that Nevergrad is a framework and not a single algorithm, and it has an impressive list of optimizers.

Back in the day before autograd optimizers became a commodity, I used Nelder-Mead and the likes heavily. To this day, I still use gradient-free methods for cases where the first derivative is discontinuous (but I suspect that e.g. Pytorch has some black-magic for those cases).