LLMs generate text one token at a time. That sounds simple. But without KV Cache, every new token...
LLMs generate text one token at a time.
That sounds simple.
But without KV Cache, every new token would repeat a lot of old work.
That is why inference optimization starts with keys and values.
Core Idea
The KV-cache is the single most important optimisation in LLM inference — and the reason real-time...
KV caches are one of the most critical techniques for efficient inference in LLMs in production.
How transformer inference actually works under the hood — and why KV cache is the single most...
A practitioner's map of KV-cache economics and the attention variants built to shrink it - GQA, MLA, linear/SSM, hybrid…
FP8 and INT8 KV caches cut attention state ~50%, but they shift the target model's logit distribution — and that can quietly…
An explanation of the KV cache memory problem in production LLM serving and how PagedAttention (the technique behind vLLM) solves…
