Episode Details
Back to Episodes“Astra can do a concerning amount with no chain of thought” by Neel Nanda
Description
TLDR: Astra has 8.6x better odds of doing a reasoning task without CoT than the next best model (Fable 5.1), and can do 7.2 serial arithmetic steps in a forward pass vs 4.1 for the next best model (Gemini 3.8 Flash/Fable 5.1)
Epistemic status: Heavily LLM-dependent research, and the precise results are somewhat sensitive to researcher decisions, but I’ve done enough sanity checks that I’d be surprised if the core claims were misleading
One of the most striking things in the Astra report was the massive jump UK AISI found in no-CoT reasoning abilities. I was somewhat suspicious, given the size of the jump, and the many ways this kind of measurement can be misleading. Conveniently, I’ve independently been making my own no CoT reasoning benchmark and tried it on there!
Unfortunately, it replicates. Astra is a massive jump, and disproportionately for no CoT reasoning:
No CoT Reasoning Index (NCRI) vs Epoch Capability Index (ECI) - NCRI represents ability without verbal reasoning, ECI represents overall model capability[2]. 10 NCRI points is a doubling of the odds of solving a problem. Astra represents a significant increase in NCRI, beyond what its overall capability improvements predict, though recent models were also [...]
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Outline:
(01:39) Executive Summary
(03:43) Measuring No CoT Reasoning
(06:13) What Is Astra Actually Good At?
(08:49) Quantifying Serial depth
(10:51) Serial Depth on Factual Recall
(11:50) Discussion
(14:08) Appendix: No-CoT Reasoning vs Controllability
(17:07) Appendix: Does Astra Benefit From Many Tokens For Serial Depth?
(18:22) Appendix: Do Open Weight Looping Models Get Disproportionate No-CoT Reasoning?
(20:13) Appendix: Astra (Almost) Pareto-Dominates Fable 5.1
The original text contained 12 footnotes which were omitted from this narration.
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First published:
September 9th, 2026
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Narrated by TYPE III AUDIO.
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