Unverified50% confidenceFactExact time
LMDeploy, combined with quantization techniques, quantizes the KV Cache data type from float to int, compressing the occupied space at the cost of some precision.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/31/2026
First Seen
Valid until: 1/29/2027
Sources
LLM Inference Bottlenecks and KV Cache: Core Mechanisms and Mainstream Optimization Approaches
bilibili先进编译实验室10/20/2026
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UnverifiedvLLM引入PagedAttention技术将KV Cache分割为固定大小物理块按需分配，而llama.cpp采用预分配策略在模型加载时一次性保留完整KV Cache空间74% similarUnverifiedDA operates at the computational logic layer and is orthogonally complementary in optimization dimensions to KV cache compression techniques that operate at the storage-transfer layer, such as quantization and eviction, and can be used in combination.70% similarUnverifiedINT4 quantization can further compress the KV Cache to 0.5 bytes, but may require calibration data to ensure accuracy.69% similarUnverified分层存储卸载offloading实践在llama.cpp、DeepSpeed-Inference等工具中已有类似应用68% similar
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