Nace AI Open-Sources Drex Max v1: A 27B Decision Model That Runs Locally on Apple Silicon

What happened

Drex Max is its most capable decision model, and it now runs on your own hardware. The release ships bf16 weights, a Q8_0 GGUF , an affine Q4 checkpoint and forks of llama.cpp and Ollama .

A top-tier decision model you can now run offline on a Mac. For developers, Drex Max open weights (a model whose trained parameters anyone may download) mean routing, classification and policy checks can stay on a local machine.

TL;DR Size: Dense 27B parameters, 262,144-token window (16,384 by default), up to 255 options per question. Runs on: NVIDIA GPU (a chip built for many calculations at once, used for graphics and AI) with Python (H100 bf16, or L40S 48 GB in 8-bit).

Apple Silicon Macs with 24 GB+ (affine Q4) or 48 GB (Q8_0 GGUF). Performance: 67.52 on the public Decision Index 0.4, 6.27 points ahead of Drex v2.0 (self-reported). Apple is a software and consumer electronics company based in Cupertino.

Drex Max is a decision model from Nace.AI that answers typed questions about a given context. You pass a state (text, JSON or images) plus named questions.

The model returns a probability for every option in one forward pass. omni_parse_bench · scores text, tables & layout · open source Star on GitHub → Sponsored Questions come in 3 types: choice among named options, yes/no, and an ordinal score.