Benchmarking MicroPython

16 ibobev 7 7/31/2025, 9:41:55 PM blog.miguelgrinberg.com ↗

Comments (7)

jononor · 12m ago
This should not be used to conclude on the viability of using MicroPython for numeric type tasks. For that one should at least take into account the following:

Integers are much faster than floats (floats involve a pointer and a heap allocation, integers are stored in a single word/object).

array.array is preferred over list for something like sort. Continuous memory representation versus linked list.

MicroPython has on-board "JIT" (native/viper emitters), have to explicitly annotate the function. Should give 4-10x improvements for this case.

MicroPython has an on-board assembler, so one can write ARM assembly and get that to a function.

MicroPython also has support for C modules, which expose a Python API. Including dynamic native modules which can be installed at runtime with the package manager.

mbirth · 7h ago
I'm missing testing the different emitters as demonstrated here: https://www.kickstarter.com/projects/214379695/micro-python-...

Not sure whether they're supported on all the architectures, though.

wewewedxfgdf · 2h ago
As the author points out, performance is pretty much irrelevant - it is a rewrite of python prioritizing memory usage.
zem · 2h ago
would have been nice to see benchmarks against the equivalent c code running on the same microprocessor, not against micropython code running on different hardware. the post just told me that microprocessors are slow, not how well micropython performs.
mrheosuper · 4h ago
Generate 2000 random numbers and sorting them using bubble sort on 160Mhz 32bit mcu takes 80 seconds ? This is exactly why micropython is a toy.
snvzz · 6h ago
>pico 2w

ARM or RISC-V?

drewcoo · 8h ago
Somehow, I don't mind that the code blew the stack because it was recursion without memoization. Blowing the stack should be a pretty clear sign to figure out why and fix it.