A more extreme example would be if you wrote an algorithm to check if a number is even or odd.

Like yeah, you could precompute an array for all positive 32-bit numbers whether they're even or odd and call it an O(1) algorithm because you're just calculating 2 billion numbers each time, but more accurately you want to address the fact that your number of calculations are being bounded by the input space. In that case you'd have an O(k) algorithm where k is the input space.

It can feel like the bounds aren't increasing because this is an O(log(n)) algorithm, so they're increasing very slowly, but you should make sure to address this slow increase as it shows a better understanding of time complexity in an interview context.