Unverified50% confidenceFactExact time
The KV cache is the Key/Value tensors caching historical tokens during large model inference, and its size grows linearly with the number of concurrent requests x sequence length x number of layers, often taking up more VRAM than the weights in long-context multi-user scenarios.
1
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50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
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Related Claims
UnverifiedKV Cache is the Key and Value tensor data from each layer of Attention that the model saves.80% similarUnverified语义缓存将历史请求转化为向量嵌入存储在向量数据库中，通过余弦相似度超过阈值时直接返回缓存结果，GPTCache已将该能力产品化70% similarVerifiedvLLM uses PagedAttention for KV Cache management63% similarVerifiedThere are generally two approaches to implementing persistent memory: the vector database approach (retrieving by semantic similarity) and the structured storage approach (saving in key-value pair format).61% similarUnverifiedLong-term memory can be updated to a vector database, which is a RAG implementation that works together with an external file system to support an Agent's state management.61% similar
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