Parallel: Decisions Fast (free)

Decisions Fast is Parallel's web-grounded Decisions model. Instead of generating text, it reads the content passed as state (text or JSON), researches the live web, and returns typed answers to named questions: the probability of yes for a yes/no question (noul), a choice with per-option probabilities (choice), or a level on an ordered rubric (score), with per-question refusals and request-level citations to the sources it used.

It suits fact checks, entity screening, and classification that depend on current information rather than only on what the caller supplies. A request can carry up to 100 questions about the same state, with up to 32,000 tokens per question including the shared state.

Decisions Fast is Parallel's web-grounded Decisions model. Instead of generating text, it reads the content passed as state (text or JSON), researches the live web, and returns typed answers to named questions: the probability of yes for a yes/no question (noul), a choice with per-option probabilities (choice), or a level on an ordered rubric (score), with per-question refusals and request-level citations to the sources it used.

It suits fact checks, entity screening, and classification that depend on current information rather than only on what the caller supplies. A request can carry up to 100 questions about the same state, with up to 32,000 tokens per question including the shared state.