Nace AI 发布 Drex 技术报告：27B 决策模型以判别式推理对打前沿 LLM
Nace AI 发布 Drex 技术报告，介绍用 RLAF 训练的开源决策模型，其中 27B 的 Drex Max 在 Decision Bench v4 上与 GPT-6 Sol 统计持平，且不生成任何 token。
Rohan Paul· @rohanpaul_ai · X·2026-11-06 22:29· 59 分钟前AI 评分53
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Nace AI 发布 Drex 开源决策模型技术报告，作者评价其用 27B 模型只做选择不做生成，专攻 Agent 中的大量小决策。Drex Max 在 Decision Bench v4 上与 GPT-6 Sol 统计持平，单次前向传播即输出各选项概率；成本 $0.06/1K 决策、延迟 183 ms，对比 Claude Opus 5.5 的 $10.17 和约 3.5 秒。
正文 · 原文
This is a brilliant release from @NaceAI .
It goes after the costly part of AI agents, the thousands of small choices, with a 27B model that only picks and never writes.
- Nace AI’s 27B Drex Max statistically ties GPT-6 Sol on Decision Bench v4 without generating a token.
- It reads a context and question, then returns one probability per supplied option in a single forward pass.
- Its RLAF training rewards verified answers plus a reasoning judge’s probabilities, while a KL penalty limits drift from supervised training.
- Drex Max costs $0.06 per 1K decisions at 183 ms, against $10.17 and about 3.5 seconds for Claude Opus 5.5.
Without chain-of-thought or tools, it answers 21% of sampled HLE questions against 56% for Opus.
How are Decision Models Trained? Today, we are publishing the Drex Technical Report for the developer community! 🚀 Discover details on how the State-of-the-art Open-Source decision models are trained with RLAF. Build more at: https://console.nace.ai/ (try for free) P.S. Drex Max 1.1 and Drex for Finance are closed sourced and designed for enterprise use-cases在 X 查看被引用的帖子
来源：Rohan Paul · x.com
来源：RadarAI · aihot.news