Verified90% confidenceTradeoffExact time
The VRAM occupied by KV Cache grows linearly with sequence length.
7
Sources
90%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
Related Claims
VerifiedThe VRAM usage of KV Cache grows linearly with sequence length; for a 70-billion-parameter model using GQA, the KV Cache usage can reach tens of GB when processing 100,000 tokens.82% similarVerifiedKV缓存将已计算的Key-Value矩阵存储在显存中实现增量计算，代价是显存占用随序列长度线性增长79% similarVerifiedThe size of the KV cache grows linearly with context length, and VRAM consumption increases significantly when processing longer texts.77% similarUnverifiedIn autoregressive inference, the memory footprint of the KV cache grows linearly with sequence length and may equal or exceed the weight volume in long-context scenarios.75% similarUnverifiedThe KV cache grows continuously with sequence length, delivering powerful long-range retrieval capability at the cost of memory that cannot be digested into the model itself.74% similar
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