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Since Nim compiles to C, porting it to new platforms is surprisingly easy. I did it a few years ago for 16-bit DOS (OpenWatcom): https://github.com/Ronsor/Nim/tree/i086-and-watcom.

Nim seems underrated. A nice balance of utility, longevity, speed, and coding niceness.

oh nim nim nim nim nim, fucking nim

shoutout if you got that [reference](https://youtube.com/watch?v=Z7PH36ZAao4)

Happy to see more Nim projects on HN!

I don't know if AI code gen helped with this particular project, so please forgive my small tangent; Claude Code is surprisingly good at writing Nim. I just created a QuickJS + MicroPython wrapper in Nim with it last week, and it worked great!

Don't let "but the Rust/Go/Python/JavaScript/TypeScript community is bigger!" be the default argument. I see the same logic applied to LLM training data: more code means more training data, so you should only use popular languages. That reasoning suggests less mainstream languages are doomed in the AI era.

But the reality is, if a non-mainstream language is well-documented and mature (Nim's been around for nearly 20 years!), go for it. Modern AI code gen can help fill in the gaps.

tl;dr: If you want to use Nim, use Nim! It's fun, and now with AI, easier than before.

Nice to see more embedded language options!