Verified75% confidenceFactExact time
KVCache is a mechanism in the Transformer architecture that caches the Key and Value vectors of all previous tokens to avoid redundant computation, with its memory footprint growing linearly with context length.
3
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75%
Confidence
Long-term
Relevance
9/11/2026
First Seen
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VerifiedKV 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79% similarUnverifiedThe 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.75% similarUnverifiedAutoregressive models use KV Cache to cache the Key and Value matrices of historical tokens, with memory usage growing linearly with sequence length.73% similarUnverifiedIn standard Transformer inference, generating each new token requires accessing the key-value vectors of all historical tokens, and the memory footprint of the KV cache grows linearly with sequence length.73% similarVerifiedThe KV cache is a core data structure in Transformer autoregressive inference, and its size is approximately 2 × number of layers × number of attention heads × head dimension × sequence length × precision bytes.72% similar
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