Nace AI Open-Sources Drex Max v1 Decision Model for Local Use
Nace AI has open-sourced Drex Max v1, a decision model that outputs probability distributions over options via a single forward pass instead of generating text. Featuring a hybrid architecture of Gated DeltaNet and full-attention layers, it outperforms competitors on public decision benchmarks and supports efficient local deployment on hardware like Apple Silicon.
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▲ Marktechpost AI · 2026-11-01 08
▲ Nace AI just open-sourced Drex Max v1, so its top decision model now runs on your own hardware, including Apple Silicon Macs.
The key idea is that Drex Max does not generate text. It reads a state (text, JSON or images) plus typed questions, and a 255-way readout returns a probability for every option in one forward pass. The 27B backbone mixes 48 Gated DeltaNet layers with 16 non-causal full-attention layers.
Nace reports 67.52 on the public Decision Index 0.4, versus 61.25 for Drex v2.0 and 57.96 for Jev 1.13.0. JevBench lands at 92.2%. It is a trade-off though: the GGUF, Q4 and MLX paths are text only, and its weakest vision score is R-Bench-M at 38.6.
Weights are under the Nace AI Open RAIL-M license. An affine Q4 build runs on 24 GB Macs, the Q8_0 GGUF (27.25 GB) needs 48 GB, and the context window goes up to 262,144 tokens......
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