JEV-27B: open System 1 decision layer grafted onto Qwen3.8-27B
AutoTrust AI's Apache-2.0 open-weights decision model: fast calibrated System 1 decisions on a frozen Qwen3.8-27B backbone, trained in ~9.2 hours on a single B200 while preserving the base model's System 2 generation path.
Why it matters
The Jev decision-model idea goes self-hosted and cheap-to-reproduce: one GPU-day of training adds a classification/scoring head without touching the reasoning model underneath - a pattern any team can copy onto their own backbone.
What you could build with it
A research group can reproduce the recipe on its own open model: freeze the backbone and train a fast decision head for a classification task in about one GPU-day.
First spotted on newsletter: source.
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