Verified75% confidenceFactExact time
Caching in large model services is generally divided into two levels: semantic caching and prompt prefix caching (KV Cache).
3
Sources
75%
Confidence
Long-term
Relevance
10/4/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedThe KV Cache mechanism can cache repeated prefix content, and the more concise the system prompt, the higher the cache hit rate.73% similarUnverifiedPrompt caching technology stores KV matrices in high-speed memory, and when the next request contains the same prefix content, it reads directly from the cache, skipping recomputation.72% similarUnverifiedThe KV Cache mechanism reduces token costs in long-context, high-frequency-call scenarios by reusing already-computed intermediate results to avoid re-executing forward inference on the same text.71% similarUnverifiedCache-to-Cache (C2C) proposes that models bypass the text intermediate layer and conduct semantic transfer directly at the KV Cache level.70% similarUnverified语义缓存通过将用户请求转化为向量嵌入，在向量空间中计算语义相似度，将语义相近的问题映射到同一缓存结果，从而减少模型调用次数和Token消耗70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/973303API
curl https://kongchang.com/api/v1/knowledge/claims/973303MCP
get_claim(id=973303)