They don't have the same goals, nor characteristics. Numba and cython are rarely used to write the entire program, you usually apply them on your bottleneck, a

They don't have the same goals, nor characteristics. Numba and cython are rarely used to write the entire program, you usually apply them on your bottleneck, and compile just this part. Also JIT, like for numba or pypy, compile when the program runs, but projects like cython and nuikta compile ahead of time. The performance characteristics are very different, since the former need a warmup but the latter don't, however they need to be manually built. Solutions like cython or mypyc require type hinting for getting the best speed up. All of them except nuikta target better perfs, some in general (pyston, mypyc, cython), some targetting specifically numerical calculations (numba). nuitka doesn't care about any of that, it takes regular Python code and compiles it. While it does provide some speedup (up to 4x), it's not the goal at all. The goal of nuikta is to able you to ship your python program as a standalone executable to the end user. It's the most reliable way to do it, as, just like the tag line says, it's "extremly compatible". I've yet to find a Python program that nuikta couldn't compile, including one with PyQT + numpy. It's very good at it.