the "good scaling" is due to variational inference, which turns inference problems into optimization problems, but one has to verify the variational approximation holds, etc.

In my experience, Pyro (generally variational inference) is more like a Bayesian optimization than full inference, since it will simply miss multimodality or non-Gaussian tails, etc.