It’s definitely early days for Mojo. I plan to talk to Chris about how he plans it to become a true Python superset that will run existing Python code out of the box.
So far, Mojo is a separate language (they have struct but not class, Int but not int, etc.), and their “CPython compatibility” strategy involves calling a helper function that you pass the name of a module, and it will import that module and execute it in CPython, returning a Mojo proxy object. It then treats CPython as a separate language runtime and when values are passed between Mojo and CPython they are “marshalled” (boxing/unboxing Int/int, etc.). This is syntactically very smooth, because Mojo and Python have compatible syntax (so you can write e.g. x+y where x is a Mojo value and y a CPython object), but doesn’t speed up running CPython at all.
I presume that the reported speedups on PyTorch etc. are obtained by rewriting key parts of the PyTorch kernel in Mojo, applying the optimizations shown in the notebooks on the Mojo site.