I have never written anything “production” grade with Julia, so do take my opinion with a grain of salt. However, I did once try to translate a simple algorithm

I have never written anything “production” grade with Julia, so do take my opinion with a grain of salt. However, I did once try to translate a simple algorithm library from Python into both Nim and Julia. Julia was no faster than Python with my initial naive implementation. After consulting the forum and getting help, I did manage to get it running fast. My impression of Julia is that it can be incredibly fast but it takes work to get to that stage. In contrast, with Nim, my code looked nearly identical to my Python code (i.e. quite simple) and ran fast from the start. This has been my general impression of Nim after doing a few projects in it: you write clean, readable code and get fast code out. There is no step 2. With respect to numerical algorithms, Nim has good support for BLAS and LAPACK. I personally haven’t used them, so I can’t comment. Nim’s metaprogramming allows for things like this [1], which is a macro library that translates between idiomatic Python and Nim. While I don’t use it myself (I find Nim’s idioms to make sense for Nim) it does make the transition a lot easier. [1] https://github.com/Yardanico/nimpylib https://github.com/Yardanico/nimpylib