Hi, a while ago I was evaluating Pharo as a platform for interactive data exploration, mining and visualization. I was fairly impressed by the tools offered by the Pharo distribution, but I had a general feeling that the platform was a little slow, so I decided to set up a small benchmark, given by an implementation of K-means. The original intention was to compare Pharo to Python (a language that is often used in this niche) and Scala (the language that we use in production), but since then I have implemented a few other languages as well. You can find the benchmark here https://github.com/andreaferretti/kmeans Unfortunately, it turns out that Pharo is indeed the slowest among the implementations that I have tried. Since I am not an expert on Pharo or Smalltalk in general, I am asking advice here to find out if maybe I am doing something stupid. To be clear: the aim is *not* to have an optimized version of Kmeans. There are various ways to improve the algorithm that I am using, but I am trying to get a feeling for the performance of an algorithm that a casual user could implement without much thought while exploring some data. So I am not looking for: - better algorithms - clever optimizations, such as, say, invoking native code I am asking here because there is the real possibility that I am just messing something up, and the same naive algorithm, written by someone more competent, would show real improvements. Please, let me know if you find anything Best, Andrea