Best Decision Models, Ranked
A decision model answers typed questions (choose one option, score on a rubric, yes or no) with a probability for each allowed answer instead of generating text. Models are ranked by their Full score on the Jev Decision Index, a third-party board of 37 benchmarks with private held-out sets, until scores from our own Metatext Decision Benchmark are published.
Ranked list
Scores, calibration (ECE) and latency from the Jev Decision Index; cost per 1,000 decisions at 200 input tokens each. Updated daily.
More decision-model rankings
Frequently asked questions
What is the best decision model?
Decision Index scores are being loaded; this ranking fills in once they are.
How is a decision model different from an LLM?
An LLM generates text. A decision model returns a probability distribution over the allowed answers for each typed question, so its output can be thresholded, audited and calibrated without parsing text.
Is the most accurate decision model the best choice?
Not always. Calibration (how far stated confidence is from the real hit rate), latency and cost per 1,000 decisions often matter as much; see the calibration and cost rankings.