Uniform precision does not really give constant prediction error from -1 to +1. You can see this by using Design Evaluation in JMP to look at the prediction variance of a uniform precision design. It is, of course, very low and flat for a large proportion of the design space.
Rotatability might seem like it adds no advantage, but that is not the case. Rotatability is achieved by setting the axial points at a certain level. This improves the prediction variance throughout the design space.
To illustrate, I created a 2 factor rotatable uniform precision CCD (5 center points) and a 2 factor orthogonal CCD with 5 center points. The ortogonal CCD will use a different axial distance. I then used the Compare Designs platform in JMP. Look at the prediction variance profile and fraction of design space plot. Although the designs are similar, the rotatable CCD performs better in terms of prediction variance.
Is this enough to worry about? Maybe not, but this difference is even more extreme when compared to an on-face central composite design, which it seems most people use (if using a central composite design).
Ultimately, the choice of the axial levels does have some impact on the prediction variance and the power of the design. Practicality does usually trump these mathematical considerations, but there are mathematical differences.
Dan Obermiller