Unverified50% confidenceSolutionExact time
llama.cpp的--cache-type-k q8_0 --cache-type-v q8_0参数可将KV Cache从FP16量化到8-bit，减少约一半缓存显存占用
1
Sources
50%
Confidence
Long-term
Relevance
8/27/2026
First Seen
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Verifiedllama.cpp通过GGUF格式对模型权重进行4-bit、8-bit等量化压缩，大幅降低显存和内存占用72% 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% similarUnverifiedllama.cpp uses quantization technology to compress model weights from 32-bit floating point to 4-bit or 8-bit integers, lowering hardware requirements so that consumer-grade GPUs and even pure CPUs can run models with billions of parameters.69% similar
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