A big reason people separate this out is because it was only a short time ago that AI models were noticably and uniquely bad at this. I don't say this to be like "oh so imagine where theyll be in x amount of time", rather that this thing that was once a serious limitation of the technology is slowly being compensated for by larger and better trained models
You can't just defer this decision to the three.js program because you need to understand this sort of relationship yourself if you're going to suitably place objects (and your own view) in a three.js scene in the first place. Building a complex scene involves making hundreds, or more, of decisions about where to place coordinates in 3d space.
This example is underspecified (e.g. what are the shapes and sizes of the objects and what is the angular width of your view) but it illustrates the problem. Even with a good intuitive understanding of 3d space, we would struggle with this. LLMs are not calculators, so it's surprising if they manage it.
Are you sure about that? Presumably the spatial concept of "inside" and the computer memory concept of "inside" have different contextual embeddings in an LLM, not so different from how our brains have different neural activation patterns when we use different concepts. Unless you think that "the same kind of inferential activity" also applies to human neurons firing.