We present a new training-free method for 3D-aware object edits on images using pretrained text-to-image diffusion models. 3D edits, like translation, rotation and scale, are implemented by lifting the activations of the diffusion model to 3D using depth information. In this paper, we present our method, followed by results on both real and generated images, and a comparative user study to position our method with respect to relevant work. We further illustrate compelling 3D applications of our method such as object editing in scenes and camera movement.