There will always be an edge to these massively operated central models that you can't easily run at home, due to compute and cost. Things like 4-bit quantization will help making these foundational models significantly easier to operate on smaller hardware, and of course you might not need a foundational model for manby local usecases, but maybe a smaller, more specialized LLM is enough (those can even be trained by the bigger models).