Unverified50% confidenceTradeoffExact time
采用INT4量化可将700亿参数模型显存需求压缩至约40GB（2张A100），但会带来约3-5%的性能损耗
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/6/2026
First Seen
Valid until: 10/4/2026
Sources
企业为何自研AI Agent？安全隐患与自主可控实践解析
bilibili马小洋qwer7/3/2026
Related Claims
Unverified一个原始需要80GB显存的700亿参数模型经4-bit量化（Q4_K_M档）后仅需约40GB内存，推理质量在多数基准测试中损失通常在3%-8%以内81% similarUnverified量化可将700亿参数模型的存储体积从FP16的约140GB压缩至INT4的约35-40GB，能在单张RTX 4090配合CPU内存卸载的消费级硬件上运行79% similarUnverified使用INT4量化技术可以将20B模型体积从约40GB缩小到约10GB78% similarUnverified千问3.5-9B包含约90亿个可训练参数，经4-bit量化后模型文件大小可压缩至约5-6GB76% similarPartially Verified标准的FP32模型每个参数占用4字节，而INT4量化将其压缩至0.5字节，理论上可实现8倍的内存节省76% similar
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