# RLAF

Drex turns choosing into a single forward pass: given a context, a question and a set of options, the model returns a probability for every option instead of parsing text written by a large model. Drex Max, the largest of four open decision models, scores 67.52 on the public Decision Index 0.4.1 suite against 60.70 for Jev 1.14.0, and drops less than a point when private tests are added. On Decision Bench v4 with raw image input it is statistically tied with d3-turbo and GPT-6 Sol, answering a typical request in 183 ms.

Drex turns choosing into a single forward pass: given a context, a question and a set of options, the model returns a probability for every option instead of parsing text written by a large model. Drex Max, the largest of four open decision models, scores 67.52 on the public Decision Index 0.4.1 suite against 60.70 for Jev 1.14.0, and drops less than a point when private tests are added. On Decision Bench v4 with raw image input it is statistically tied with d3-turbo and GPT-6 Sol, answering a typical request in 183 ms.

Drex replaces asking a large model to generate text and parsing an answer with a single forward pass that scores each supplied option. The largest of the four open models, Drex Max, scores 67.52 on the public Decision Index 0.4.1 suite against 60.70 for Jev 1.14.0, and drops less than a point when private tests are added. On Decision Bench v4 it is statistically tied with d3-turbo and GPT-6 Sol and 1.6 points behind Claude Opus 5.5, while answering a typical request in 183 ms.

Drex replaces asking a large model to generate text and parsing an answer with a single forward pass that scores each supplied option. The largest of the four open models, Drex Max, scores 67.52 on the public Decision Index 0.4.1 suite against 60.70 for Jev 1.14.0, and drops less than a point when private tests are added. On Decision Bench v4 it is statistically tied with d3-turbo and GPT-6 Sol and 1.6 points behind Claude Opus 5.5, while answering a typical request in 183 ms.