Why KV Cache Matters — How MQA, GQA, and MLA Make LLM Inference Faster

The article highlights the importance of KV Cache in optimizing large language model (LLM) inference. Without it, generating text would involve redundant calculations for each new token. KV Cache stores previously computed key and value tensors, allowing the model to quickly reference them instead of recomputing them. This optimization is crucial because it speeds up the autoregressive generation process, making it more efficient and faster. Understanding this mechanism provides insight into how advancements in LLM technology can lead to significant performance improvements.