What is the difference between ordinal probit and ordinal logit?

Can you explain the fundamental distinction between ordinal probit and ordinal logit models? As a practitioner in the field of finance and cryptocurrency, I'm curious about their applicability in modeling ordinal dependent variables, particularly when dealing with market sentiment or risk assessment. How do the two models differ in their assumptions, interpretation of coefficients, and the types of data they can handle?