checking model stability - Performance for different class
A consideration: I dont think A is stable since it has a huge difference between validation and test results.

Some questions before answer:


Are you using cross validating with how many folds? The best result are the mean between folds results? What is the stddev? If stddev is big, it can tell us a history.
Your folds are shuffled? I see lot of people folding when using scikit learn without shuffle since its not the default behavior.
Is your test data unbalanced? if so, its normal the difference between test and validation results.
How many examples are you using for test and how many fot test? Sometimes the stability of the model requires more examples.