Repo · Benchmarks & research
tinyjev
Offline ~0.6B System One–compatible decision model (Choice/Noul/Score with calibrated probabilities) on MLX or PyTorch—independent of hosted TypeSafe…
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A tiny jev-like model that answers Choice, Score and Noul questions in one forward pass and returns calibrated probabilities. MLX or PyTorch, fully offline, System One compatible.
decision-modeljevjev-modelmlxqwen3small-language-modelssystem-onetyped-decisionstypesafe
How builders describe it
A tiny jev-like model that answers Choice, Score and Noul questions in one forward pass and returns calibrated probabilities. MLX or PyTorch, fully offline, System One compatible.
Offline ~0.6B System One–compatible decision model (Choice/Noul/Score with calibrated probabilities) on MLX or PyTorch—independent of hosted TypeSafe Jev.
Local typed-decision models that answer Choice, Noul and Score in one forward pass on your own machine, with a Python API, local HTTP server and System One request shape.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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