Unverified50% confidenceOpinionExact time
When temperature, top_p and top_k are used in combination, their effects are hard to predict, and this is the main source of output style drift for the same prompt under different parameters.
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50%
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Long-term
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10/22/2026
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Related Claims
UnverifiedAutoregressive generation outputs are affected by sampling strategies (hyperparameters such as temperature and top-p), making it difficult to guarantee completely consistent outputs77% similarVerifiedTemperature controls the flatness of the sampling distribution; a higher value tends toward selecting lower-probability words, while Top-p dynamically narrows the candidate vocabulary set through a cumulative probability threshold.75% similarVerifiedThe non-determinism of LLMs stems from sampling strategies; the Temperature parameter controls the randomness of the output distribution, while Top-p and Top-k further constrain the range of candidate tokens.73% similarUnverifiedTop-p（核采样）通过限定候选token的累积概率范围来控制输出多样性，与Temperature配合使用可实现更精细的输出调节71% similarUnverified由于模型工具选择受上下文窗口内容、温度参数、推理链路等因素影响，相同输入在不同运行中可能产生不同的调用序列，这种非确定性是Mock难以覆盖的根本原因70% similar
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