The Palo Alto startup's flagship model scores 67.52 on Decision Index 0.4 with a median latency of roughly 183 milliseconds
Most AI models answer a question by writing. Nace AI wants its models to simply decide.
The Palo Alto startup has published a technical report titled “Towards Foundation Decision Models: Drex” on arXiv, released around November 5, 2026. Alongside it comes Drex Max, a 27-billion-parameter model built to pick from a set of options rather than generate paragraphs of text.
The pitch is speed and cost. Nace AI says Drex Max hits a median response time of approximately 183 milliseconds. Comparable systems, by the company’s measure, take between 2 and 3.5 seconds to respond.
What Drex Max actually does #
Technically, the model returns calibrated outputs tied to those user-defined choices. It does this in a single forward pass instead of using the autoregressive approach common to chat-style models.
The model is also multimodal. Drex Max accepts text, images, JSON and video as inputs. It supports a 262,000-token context window.
On benchmarks, Drex Max scored 67.52 on Decision Index 0.4. Nace AI describes that result as a new state-of-the-art among decision models.
How the models were trained #
The technical report centers on how Nace AI trained the Drex family. The company used a method it calls RLAF, combined with supervised fine-tuning and consistency losses.
Drex Max is not the only release. The full Drex model family is available, including a smaller 9B variant. The models and associated resources are being distributed through GitHub and Hugging Face.
AI, tech, and the markets they move—in one daily briefing.
Daily. Free. Join 34,000+ readers across crypto, finance, and policy.
The family ships under the Nace.AI Open RAIL-M license.
Background on Nace AI #
Nace AI is a young company. It was founded in 2024 and is based in Palo Alto.
In May 2026, the startup raised $21.5 million in seed funding. Walden Catalyst led the round, with General Catalyst also participating.
The company has already been packaging its decision technology into specific products. Those include Drex for Search and Drex for Finance.
What this means #
The interesting bet here is architectural. Much of the AI industry has spent the past few years making models bigger and more conversational. Nace AI is arguing that a large share of enterprise work does not need conversation at all.
Calibration is the quieter selling point. In enterprise settings, knowing how confident a model is can matter as much as the answer itself.
The product lineup hints at the target customers. Drex for Finance suggests banks and financial firms, where latency and auditability both carry weight. Drex for Search suggests ranking and retrieval.
The open-release strategy is the other lever. Putting the full family, including the 9B variant, on GitHub and Hugging Face lowers the barrier for developers to test the approach.
The latency and benchmark comparisons come from Nace AI itself. Decision Index 0.4 is also a specialized benchmark. The license terms will shape adoption too, as Open RAIL-M style restrictions can limit some commercial uses.
Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.