# GPT-6 Astra 传采用循环 Transformer，不增参数只加深度

- 来源：SemiAnalysis (@SemiAnalysis_)
- 发布时间：2026-09-15 10:00
- AIHOT 分数：32
- AIHOT 链接：https://aihot.news/items/cmu21e0gn04fprow2d5ciibqo
- 原文链接：https://x.com/SemiAnalysis_/status/2099679686758400144

## AI 摘要

据称 GPT-6 Astra 采用 loop transformers，不再增加参数量，而是让模型多次经过同一批层，以增加计算深度而非模型规模。SemiAnalysis 认为，实验室最清楚模型扩展方向，这一选择暗示他们在路线图和研究中对参数规模的扩展预期已不再激进。

## 正文

GPT-6 Astra reportedly gets deeper without getting bigger. The labs already know what that means for scaling.

"It's basically confirmed that GPT-6 Astra uses loop transformers, which means that instead of adding parameter count, it goes through the layers more than once. You add compute depth, but you don't increase the size of the model."

"The labs are probably the people that are best positioned to say which way models are scaling. I think that's a tell that they're not seeing parameter sizes scaling as aggressively in their roadmaps, in what they find in their research."