If your disagreement is that a constant is not appropriate here, consider the interpretation in this comparison of running a program on a slower computer A and then a faster computer B. There would be a constant difference in performance between these two computers, assuming they are in working order. So, taking the model with a single constant is appropriate for this example.
If you are saying the performance improvement is bounded below by a constant, I would ask you, what is the domain of this function? Time? So we would be talking about continuously moving a computation between different computers? The only line here is a best fit line, emergent data, so I don't understand how this could be a preferred way to talk about the situation (the alternate to an assumption), because this is suggesting the emergent structure with nice continuity features is a preferred fundamental understanding of the situation, but it's not.
Then, where you are talking about hardware performance improving up to a (assuming horizontal) asymptote. I guess this means "If hardware performance increase becomes marginal[1], there is a nonzero improvement." Or in other words, "If hardware performance increase is marginal, there is a marginal [performance] increase". Performance and improvement are both rates of change, so this is tautological.
Finally, you state that waiting for such a marginal near-zero performance increase isn't worth it. I think most people would agree this is obvious if said in simpler terms. However, this is still not disagreeing with me, because I never suggested waiting was worth it.
So, what's the disagreement?
[1] which is well-established not to be the case, so I don't think this is a relevant case to the interesting factoid about waiting to start computation
Though this does assume that X is a constant, or at least bounded below by a constant. If hardware performance improved up to an asymptote, then there would still be nonzero improvement, but it might not be enough for waiting to ever be worth it.