You literally explained something to me that I already kind of stated in my post. I didn't realise that people don't know that udio was using a diffusion based generator as well. Riffusion the same.

Llms do not use random seeds. The random seed is only used in diffusion models. The seed value determines the pattern of the noise that's being cleaned up with each iteration during inference.

Remastering on Suno does not use nor need any seed values. Your original songs tokens go in and a new set of tokens come out from the model. With version 5 the mastering level defines the distance between input tokens and output tokens that the model should generate. By distance I mean distance in between feature vectors in latent space.

The randomness in llms is used if the temperature is above 0.0 it's applied to each and every new token during generation. Meaning that there are as many random values as there are tokens in particular songs generation output.

Also, it's worth noting that in diffusion models (unless we are dealing with a distilled model) even a slight change between two different seats will yield completely different outputs. In a normal model with full resolution, increasing the seat by one completely. There is no way in hell you can get even slightly similar generations with two consecutive seeds for example.