a) we don't actually know what the prices will look like yet,
b) what about same weights + huge context? or, same weights that you'd run on 128gb/256gb, but multiple models running for different tasks?
Longer context also slows token prediction proportional to the context size. If it wasn't regularly referenced then there would be no need to keep it in RAM.
Usually the pitch for more memory is "I can run a massive model/context and get my answer in a while instead of next weekend from disk".