Checked fact 320130 Oct 2026Research

The paper observes that inference is often limited by memory bandwidth and communication rather than arithmetic, so spare compute is often available.

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We additionally observe that inference from large models is often not bottlenecked on arithmetic operations, but rather on memory bandwidth and communication, so additional computation resources might be available.

What the source said when we opened it, on 30 Oct 2026.

The source

Fast Inference from Transformers via Speculative Decoding
arXiv (Leviathan, Kalman, Matias) · 2022-11-30

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Checked by the notis newsroom on 30 Oct 2026, against the source above.

In the story

How speculative decoding lets a small model draft and a large one check 30 Oct 2026

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“The paper observes that inference is often limited by memory bandwidth and communication rather than arithmetic, so spare compute is often available.” ai notis, checked 30 Oct 2026. Source: Fast Inference from Transformers via Speculative Decoding (arXiv (Leviathan, Kalman, Matias)). https://ainotis.com/c/3201

As a reference (APA style)

ai notis. (2026, October 30). The paper observes that inference is often limited by memory bandwidth and communication rather than arithmetic, so spare compute is often available [Checked claim 3201]. ai notis. https://ainotis.com/c/3201

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