Prism reports "perfect fit' when the curve goes through every point. The sum-of-squares is 0.0, and R2 is 1.00.
If you are testing nonlinear regression with made up values, add some random scatter to make a better example.
If you are fitting actual data, and the fit is perfect, you either got very lucky or have very few data points. It is not possible to compute the standard errors and confidence intervals of the parameters when the fit is perfect, nor is it possible to compare models.