Logistic regression is concerned about modelling log-odds, i.e. logits. Hence, the odds of the computed probabilities can be interpreted accordingly. However, when estimating a probit model, one could also take the probabilities and compute odds. However, probit is not based on modeling odds but on the cdf of the standard normal.
So, does it make sense to compute these odds for probit models anyway? If yes, how can it be interpreted and what is exactly the difference in interpretation compared to odds in logistic regression?