korrents

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As reasoning models and agents retain more tokens for longer, KV-cache size and attention cost become the main constraint on scaling context.

Drawn from what Sebastian Raschka said

SubjectstransformersLLMs
What this subject means

transformers The architecture that dropped recurrence in favour of attention, and that almost every large model since is built on.

Mental modelBottlenecks

What Sebastian Raschka actually said

  1. Sebastian Raschka AI research engineer working on large language models
    As reasoning models and agent workflows keep more tokens around (for longer), KV-cache size, memory traffic, and attention cost quickly become the main constraints, and LLM developers are adding a growing number of architecture tricks to reduce those costs.

    Where this was said

    ↗Recent Developments in LLM Architectures: KV Sharing, mHC, and Compressed Attentionmagazine.sebastianraschka.com

    16 May 2026

    All 2 korrents from this piecethis one is 1st

Added to korrents 20 Sept 2026 · How quotes work · Something wrong? Tell us

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