Raschka deep-dive: GPT-6 Astra, looped transformers, and the hidden chain-of-thought question
AxSaucedo · x · 2026-09-15
Sebastian Raschka published a long-form analysis of OpenAI's new GPT-6 Astra and the research behind looped transformers.
- Hands-on impressions: He calls Astra the best model he has used so far, leapfrogging GPT-5.6 across writing, math, and coding, and disproportionately strong at 3D rendering and animation demos.
- Core topic: A detailed explainer of looped transformers — reusing the same transformer blocks over multiple iterations to create implicit recurrent depth and hidden internal reasoning chains.
- Hidden CoT: He examines rumors that Astra "hides" its reasoning trace, how that relates to recurrent-depth architectures, and highlights new insights from recent research papers on the topic.
Related event: Raschka Deep-Dives GPT-6 Astra's Looped Transformer Architecture(2 posts)→
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