I thought this too, but it seems that is not the case. I could not remember the reason I saw why so I googled it (AI excerpt).

Large Language Models (LLMs) are not perfectly deterministic even with temperature set to zero , due to factors like dynamic batching, floating-point variations, and internal model implementation details. While temperature zero makes the model choose the most probable token at each step, which is a greedy, "deterministic" strategy, these other technical factors introduce subtle, non-deterministic variations in the output

You were probably thinking about this piece on nondeterminism in attention by Thinking Machines: https://thinkingmachines.ai/blog/defeating-nondeterminism-in...