exactly. visual information is more compressable than natural language: much of it boils down to locality, whereas language forms are highly pareto distributed plus the conceptual system is a huge hypergraph, so it's rather the opposite of "local" organisation of information.
2D still images, at least the sort that humans are familiar with, are more limited in terms of representation power and thus more amenable to compression into network weights.
Perhaps models representing 4D phenomena (3D entities with time dimension, e.g. videos of real 3D models) would be more comparable in size to natural language models. Since LLMs can also represent abstract and unreal entities, while 4D representation can represent more details, it's hard to say which kind of models is richer.