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PagedAttention and the KV Cache, Plainly: Why Memory, Not FLOPs, Caps Your Concurrency

One 128K-token conversation with a 70B model needs 40 GiB of GPU memory — not for the weights, for the memory of the conversation itself . An 8B model on the same GPU fits 56 such conversations at once; the 70B model in FP8 fits zero. Same GPU, same 8K-token chats, and the difference is not speed.…

Read the full story at DEV Community — Machine Learning ↗

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  1. 2026-11-10 17:03 · DEV Community — Machine Learning
    PagedAttention and the KV Cache, Plainly: Why Memory, Not FLOPs, Caps Your Concurrency

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