What inference can we draw from the frequency distribution of thresholds? I've the probability scores of positive class of two models. The frequency distribution of those probability scores(thresholds) are like this 

Model #1


Model #2


It's a binary classification problem. And the thresholds obtained are from the test data. The stats in the confusion matrix are nearly same for two models. Can we say the Model #2 is doing well in separating classes? What other conclusion we can draw from the frequency of the thresholds.
I'd say the model 1 is performing really well. If you can use different colors while plotting for positive and negative classes, then you should be able to see the difference. When you are trying to do binary classification, the distributions of negative and positive classes should be dipping in the mid region where as Model 2 is the opposite.