Can repeated runs of a Las Vegas algorithm equate to a better Las Vegas algorithm?
Monte Carlo and Las Vegas algorithms are equivalent and this question is more naturally asked in terms of the former so I will pretend you asked about Monte Carlo.

Any Monte Carlo algorithm can be run multiple (say, a constant number of) times to amplify the probability of success while slowing down the algorithm. And in fact you can achieve any fixed probability of success $&lt; 1$ while slowing down by a constant factor.

Where you "cheat" is that you adopt the convention of ignoring the constant factor in run time while simultaneously caring about the constant probability of success. As the probability can be freely adjusted by multiplying run time by a constant, caring about its particular value is equivalent to caring about the constant factor in run time so big O is inappropriate in this situation.