Unverified60% confidenceFactExact time
双重量化对每64个参数共享的FP32缩放因子进一步量化为FP8格式，使每个参数的量化开销从0.5bit降低到约0.127bit
2
Sources
60%
Confidence
Long-term
Relevance
8/26/2026
First Seen
Sources
Related Entities
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Unverified140GB的FP16 70B模型经4-bit量化后可压缩至约35-40GB，通信开销降低约75%；2-bit量化可压缩至约18GB但带来精度损失78% similarUnverified以Q4_0格式为例，每32个FP32权重被打包为一个量化块，包含一个缩放因子和32个4bit整数，平均每参数约占4.5bit，内存占用缩减至原来的约1/877% similarUnverified量化将FP32权重转为INT8或FP16，在保持音质前提下减少计算量和内存带宽压力76% similarVerifiedFP8量化可将7B模型权重从约14GB（FP16）压缩至约7GB75% similarUnverified2.4万亿参数模型在FP32下约需9.6TB显存，BF16约需4.8TB，INT8约需2.4TB，INT4约需1.2TB75% similar
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