Unverified75% confidenceFactTime unknown
传统LLM推理中KV Cache的内存管理导致60%-80%的显存被浪费
1
Sources
75%
Confidence
Long-term
Relevance
6/1/2026
First Seen
Sources
Cube Studio深度解析：腾讯开源一站式MLOps平台实战指南
githubtencentmusic
Related Entities
Related Claims
Unverified传统LLM推理中，KV Cache的内存管理导致60%-80%的GPU显存被浪费92% similarUnverifiedTraditional KV cache implementations pre-allocate contiguous GPU memory blocks of maximum length, resulting in an average of 60%–80% of pre-allocated memory being wasted.83% similarUnverifiedPagedAttention improves KV Cache memory utilization from below 40% to close to 100%.73% similarUnverifiedTraditional LLM inference engines have severe memory fragmentation issues when handling KV Cache; for a 13B parameter model, the KV Cache for a single request may occupy several GB of memory, while the actual utilization rate may be below 50%.72% similar
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