Why should it be the case that LLMs are equally comfortable in x86 Assembly and Python? At least, it doesn't strike me as implausible that working in a human-readable programming language is a benefit for an LLM that is also trained on a bunch of natural language text alongside code.

It’s not a super useful line of inquiry to ask “why” LLMs are good at something. You might be able to come up with a good guess, but often the answers just aren’t knowable. Understanding the mechanics of how LLMs train and how they perform inference isn’t sufficient to explain their behavior a lot of the time.