Unverified60% confidenceFactExact time
KV cache size is proportional to the number of model layers, the number of attention heads, sequence length, and per-head dimension, and is the primary source of VRAM usage during large model inference.
2
Sources
60%
Confidence
Long-term
Relevance
9/19/2026
First Seen
Sources
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Related Claims
VerifiedThe 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.80% similarUnverifiedThe KV cache carries the model's complete current reasoning state, and directly modifying it is equivalent to directly intervening in the model's thinking process.78% similarUnverifiedThe actual memory usage during large model inference is often 1.5–3 times the model weights, due to the overhead from the KV Cache, intermediate activations and context length.77% similarUnverifiedKV Cache技术允许模型在自回归生成时复用历史token的注意力Key-Value矩阵计算结果，使长对话推理延迟从O(n²)降低至接近线性76% similarUnverifiedIn large language model inference, KV-Cache is used to store the key-value pairs already computed in the attention mechanism, thereby avoiding repeated computation.74% similar
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