Models that answer with a probability for every option instead of a paragraph β ranked by JevBench on smarts, calibration, speed and cost per 1,000 decisions.
A decision model reads a state β a log, a diff, a ticket, a web page β and a set of typed questions: pick one of these options, yes or no, or where on this scale. One forward pass returns a probability for every option. Nothing is generated, so there's no text to parse and no answer outside the options you gave it.
They sit inside agent loops where a chat model would be slow and expensive: routing, triage, "did the tests pass", "which button next", "is this safe to run". Most are small open-weight fine-tunes you can host yourself; the original is TypeSafe AI's hosted Jev.
rollback_now99.1%page_database0.7%keep_investigating0.2%close_ticket0.0%| Model β | Score β | Intelligence β | Calibration β | Per 1k decisions β | Per month β | Speed p50 β |
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