I think what you have is a set of actual values and 2 sets of predicted values.
If so then I'd calculate the coefficient of determination.
each observation minus the average
each observation minus predicted
You'd do this for each model. I may go one step further and compare the coefficients of determination with each other. There was a paper written by Olkin and Finn called Correlation Redux that shows how to do this.
This might be my approach others may have different ideas. It's possible if you have an actual model that predicts to compare the models. All you said you had were two sets of predictions though.