KV caching explained: why it shapes GPU memory and drove the shift to GQA and MLA
blaizedsouza · x · 2026-10-12
techNmak publishes a deep explainer on KV caching: without it, each decoding step would recompute key/value states for already-processed tokens. The cache grows with sequence length, consuming GPU memory and creating bandwidth pressure—which explains the architectural shift from MHA to MQA, GQA, and MLA across the LLM serving stack.
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