KV cache cut by ~45% with near‑same accuracy
This story is from 2026-09-25. It is preserved in the archive; the latest stories are on the live feed.
Grouped Value Attention slashes transformer KV memory by roughly 45 % without hurting benchmark scores. By storing only grouped values and reconstructing keys on the fly, it eliminates the need to materialize a full key matrix during decode, cutting the persistent cache scalars dramatically. Before…
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- 2026-09-25 05:00 · DEV Community — Machine Learning
KV cache cut by ~45% with near‑same accuracy