Unverified50% confidenceFactExact time
The 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.
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50%
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Long-term
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10/13/2026
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Related Claims
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75% similarUnverifiedAutoregressive models use KV Cache to cache the Key and Value matrices of historical tokens, with memory usage growing linearly with sequence length.75% similarUnverifiedKVCache 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.75% 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.73% similarUnverifiedDuring inference, each token requires maintaining a KV cache (Key-Value cache), whose GPU memory usage is proportional to sequence length and the number of model layers.73% similar
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