Indeed, the AOT compilation leads to great speed-ups for heavy custom numeric calculations that cannot be easily vectorized in numpy, such as the raytracing logic. In cases when most of calculations are performed in an external module (written in e.g. C, Rust or Cython etc) the performance gain might be much less, but the added value here is that the high performance module itself can be written in nimic, keeping the codebase purely in Python and consolidating the codebase.
When starting with a "pythonic" code, rewrites in nimic can be substantial but so would be a rewrite in a systems language like C or Rust. Besides allowing to optimise the fast path, nimic provides low level functionality, such as pointers to pointers and bitwise operations that actually executes within CPython, for example, as in mp4 muxer implementation in dima-quant/ndsl_raytracer/src/nraytracer/minimp4.py