Comment by jmaker

This is an interesting hypothesis to test. Depending on the embedding model, such less frequently encountered character sequences in the coding domain could indeed produce less optimal tokens. A dedicated model trained from scratch on Haskell would be optimal but wouldn’t generalize well beyond that, but can serve as a deliberately overfitted baseline.

What I meant was really about the output tokens, on the API pricing level of interaction with an LLM.