It’s ordinary computational complexity reasoning: if a part of your program scales like n^2, and another like n, then for large enough n the former will overtake the latter and pretty much dominate the total cost. That said, as someone pointed out, the specifics matter too. If your total cost was something like n^2+1,000,000,000n, it would take a very big n for the quadratic term to finally make itself felt properly. So depending on the details of the architecture, and how it was scaled up in ways other than just increasing context, the scaling might not actually look very quadratic at all.
It’s ordinary computational complexity reasoning: if a part of your program scales like n^2, and another like n, then for large enough n the former will overtake the latter and pretty much dominate the total cost. That said, as someone pointed out, the specifics matter too. If your total cost was something like n^2+1,000,000,000n, it would take a very big n for the quadratic term to finally make itself felt properly. So depending on the details of the architecture, and how it was scaled up in ways other than just increasing context, the scaling might not actually look very quadratic at all.