12 KV caching techniques to optimize LLM inference, from sliding window to MLA
blaizedsouza · x · 2026-10-14
akshaypachaar shares a graphic covering 12 KV caching techniques for LLM inference optimization. KV cache stores keys/values of past tokens to avoid recomputation, but long conversations and concurrent requests balloon memory demand. Techniques include sliding window (capped cache for local attention layers), cross-layer sharing (layers reuse KV), and multi-head latent attention (caching compact representations). Paired with an accompanying article explaining why first-token latency exists by design.
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