Temperature

Temperature is a scalar hyperparameter that controls the randomness of a language model's output by dividing logits before the softmax operation. A temperature of 1.0 leaves the model's learned distribution unchanged. Values below 1.0 sharpen the distribution, making high-probability tokens more dominant and output more deterministic. Values above 1.0 flatten the distribution, increasing diversity and creativity but also raising the risk of incoherent or factually incorrect text.