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In a decision model, the state is a one-time input representation received by the model, which can be a text encoding, an image embedding, or an audio feature encoding, usually a fixed-dimension vector or tensor. Each question performs lightweight computation on the same state, so the marginal cost of multiple questions is very low.
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10/13/2026
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UnverifiedA Decision Model returns a probability or classification result for content rather than outputting long passages of text, and its structured output can be used directly in if statements in code.73% similarVerifiedThe output of a decision model is often a label or probability distribution over a finite action set, similar to a policy network in reinforcement learning, whereas generative models require autoregressive sampling over a large vocabulary.72% similarUnverifiedThe decision model evaluates state against bounded criteria and returns a decision score without producing an open-ended token stream, and runs in milliseconds.71% similarVerifiedSpeculative decoding is a lossless acceleration technique that does not alter the model's output distribution; it uses a draft model with far fewer parameters than the target model to generate candidate tokens, which the target model then verifies in parallel.70% similarUnverifiedA decision model is a type of model designed specifically for making choices among a limited set of options, with output constrained to a predefined structure, and its fundamental difference from generative models lies in the output space.70% similar
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