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SemiAnalysis 称 GPT-6 Astra 用循环 Transformer 加深而非加大

视频解读 Astra 靠重复过层增加计算深度、不增参数量,并认为这透露实验室路线图里参数规模扩张已不再激进。

SemiAnalysis
@SemiAnalysis_2026.09.16收录原推发布于 2026.09.15
SemiAnalysis @SemiAnalysis_原推发布于 2026.09.15
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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."

x.com/semianalysis_/status/2099679686758400144采集于 2026.09.16 10:20