Maybe I'm wrong, but with these diffusion models there is randomness in every sampling step too not just in the initialization and they can have 1000 steps to generate a single image.
Ah good point, this would introduce more variation if the initial noise is close, but if the initial noise is exactly the same it probably means it was initialized with the same seed and the rest of the generation will be the same since the random algorithms are deterministic.
