# Drex

Nace released Drex, a decision model for document processing that, after the parsing engine returns layout-aware Markdown, judges page by page whether text matches the page image, whether a table kept its shape and whether a ticked box survived, and triggers correction only where something is in doubt. On Nace's own parsing leaderboard, NDI plus Drex scores a Parse Index of 0.834, ahead of all 12 parsers tested, including LlamaParse Agentic at 0.820; it improves on the engine alone on OmniDocBench, MDPBench and ExtractBench, and is within noise of it on ParseBench and RealDocBench.

Nace released Drex, a decision model for document processing that, after the parsing engine returns layout-aware Markdown, judges page by page whether text matches the page image, whether a table kept its shape and whether a ticked box survived, and triggers correction only where something is in doubt. On Nace's own parsing leaderboard, NDI plus Drex scores a Parse Index of 0.834, ahead of all 12 parsers tested, including LlamaParse Agentic at 0.820; it improves on the engine alone on OmniDocBench, MDPBench and ExtractBench, and is within noise of it on ParseBench and RealDocBench.

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 for Search is a search tool for AI agents in which Drex, a decision model, decides before the agent reads anything where the answer can be: which folder, file and page, and inside a spreadsheet which table and column. Across 6 professional-work benchmarks and 529 questions, coding agents using it raised accuracy from 63.1% to 67.1%, took 62% fewer steps, used 56% fewer input tokens, and cut median time per question from 80.8 s to 35.5 s. On the 133 questions of OfficeQA Pro, all ten agent-and-model pairs took fewer turns and fewer input tokens, and eight answered more questions correctly.

Drex for Search is a search tool for AI agents in which Drex, a decision model, decides before the agent reads anything where the answer can be: which folder, file and page, and inside a spreadsheet which table and column. Across 6 professional-work benchmarks and 529 questions, coding agents using it raised accuracy from 63.1% to 67.1%, took 62% fewer steps, used 56% fewer input tokens, and cut median time per question from 80.8 s to 35.5 s. On the 133 questions of OfficeQA Pro, all ten agent-and-model pairs took fewer turns and fewer input tokens, and eight answered more questions correctly.

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.