Unverified50% confidenceFactExact time
Logprobs are the logarithmic form of the probability distribution a language model gives when generating each token; when enabled, the API additionally returns candidate tokens and their log probabilities, and pricehunt uses this to soften binary yes/no judgments into a 0~100% match percentage.
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10/14/2026
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UnverifiedLeveraging the logprobs interface of existing LLMs to request only the log probabilities of specific candidate tokens can achieve the effect of a decision model without replacing the model; OpenAI's logprobs parameter supports this mode.73% similarUnverifiedAn autoregressive language model produces a logit vector of vocabulary size at each prediction step, and its structure determines the conditional probability distribution of the next token.71% similarUnverifiedlogit函数定义为log(p/(1-p))，将概率值从[0,1]映射到(-∞,+∞)，是广义线性模型中处理二分类因变量的核心技术69% similarUnverifiedLogits are the raw unnormalized scores output by the model's final layer; after softmax they become the probability distribution over each token, and they are the most observable quantity closest to "model confidence."69% similarUnverifiedFor multiple-choice questions, the logits over each option token can be normalized via softmax to obtain a probability distribution, where a highly concentrated distribution indicates the model is more confident in the answer68% similar
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