Unverified60% 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.
2
Sources
60%
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% similarUnverifiedWhen 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% 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% similarUnverifiedKV Cache 的核心思想是缓存前面已计算的中间结果，避免每步从头计算75% similar
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