Memory Management in LLMs

Ajay Walia — Sun, 14 Jun 2026 00:00:00 +0000

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Everything about how large language models use, store, and optimize memory — from the bytes that hold model weights on a GPU to how an agent remembers a conversation across sessions. Each topic is tagged bywhen the memory is consumed. Pick a card to open the article.

Static — set before you runRuntime — scales with workloadTraining — only during trainingOverviewApp-level memory

System & Runtime Memory
How the model physically uses hardware

Agent & Long-Term Memory
How the model "remembers" across turns & sessions

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