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> A custom toolchain compiles a .py file into CPython ByteCode, translates it to a custom assembly, and produces a binary that runs on a pipelined processor built from scratch.

> Runs a subset of Python

What's the advantage of using a new custom toolchain, custom instruction set and custom processor over existing tools that compile a subset of Python for existing CPUs? - e.g. Cython, Nuitka etc?

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Compilers and optimizers are great tools for some use cases, but not all.

Just to name a few limitations:

- Many rely heavily on the CPython runtime, meaning garbage collection, interoperability, and object semantics are still governed by CPython’s model.

- They’re rarely designed with embedded or real-time use cases in mind: large binaries, non-deterministic execution (due to the underlying architecture or GC behavior), and limited control over timing.

If these solutions were truly turnkey and broadly capable, CPython wouldn't still dominate—and there’d be no reason for MicroPython to exist either.

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