It's not just 5%. If you have any API which takes a higher order function, for example a differential equation or optimization package, then even if your code is compiled and the user's input is compiled, you still have to hit Python in the middle, and that context switch can be the most costly part of an optimized code, making Numba+SciPy about 10x slower than it should be. So yeah, Python + compiled code is not a viable solution in all cases, or in fact what seems to be most of scientific computing (but not data science where things tend to not include function input).

http://juliadiffeq.org/2018/04/30/Jupyter.html