Rumor: post-hoc GQA→MLA conversion cuts Qwen 27B KV-cache memory by up to 8.4x
ChrisGPT · x · 2026-10-21
ChrisGPT reports hearing about a small AI research team experimenting with post-training Qwen 3.8 27B. Their claimed trick: a post-hoc GQA→MLA conversion that reportedly reduces KV-cache memory requirements by up to 8.4x without additional training. Unverified rumor — no paper or code attached yet — but if real, training-free attention-architecture conversion would be notable for local deployment and inference-cost optimization of open-weight models.
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