Working directly on pixels is too expensive, so modern image models compress first. A picture goes into a smaller representation that keeps what matters and throws away what does not, the denoising happens in that compressed space, and a decoder turns the result back into pixels at the end. The compressed space is the latent space, and it is where the model actually thinks.
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