Verified65% confidenceFactExact time
KV Cache is a key data structure in autoregressive generation by large models: when generating each new token the model needs the Key and Value vectors of all previous tokens, and if these were recalculated every time the cost would grow quadratically with sequence length.
3
Sources
65%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
TokenSpeed: An Open-Source Speed-of-Light LLM Inference Engine
githubGitHub Trending (daily)10/15/2026
Related Entities
Related Claims
UnverifiedThe context cache (KV Cache) is the memory area that stores the Key and Value vectors of previous tokens during inference of Transformer-type models, and its size grows linearly with context length, batch size, and the number of model layers.80% similarVerifiedWhen generating each token, a Transformer model needs to compute the Key and Value vectors of all previous tokens, and these tensors are collectively called the KV cache.79% similarVerifiedKV Cache是Transformer架构的核心推理优化机制，其显存占用量会随序列长度和并发批次线性增长76% similarUnverifiedPrefix cache reuse causes KV values to be computed in a different batch than a fresh prefill, so the KV values from a cache hit may differ at the floating-point level from those of a fresh prefill, and the difference propagates through subsequent tokens.76% similarUnverifiedWithout KV Cache, the model would need to recompute all preceding content every time a new token is generated, with computational complexity growing quadratically with sequence length.76% similar
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