Unverified50% confidenceFactExact time
Quantization compresses model size by converting 32-bit or 16-bit floating-point parameters into 8-bit integers (INT8) or 4-bit integers (INT4).
1
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50%
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Long-term
Relevance
9/12/2026
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Related Claims
UnverifiedThe core principle of quantization is to convert model parameters from high-precision floating-point representations (such as FP32's 32-bit floating point) to low-precision representations (such as INT8's 8-bit integer or INT4's 4-bit integer).80% similarUnverified推理端优化技术包括量化、知识蒸馏和KV Cache，量化可将参数从32位或16位浮点压缩为8位甚至4位整数79% similarUnverifiedINT4量化将原本由65536个不同值（FP16）表示的权重压缩到仅16个离散级别74% similarVerifiedFP32每个参数占4字节，FP16/BF16占2字节，INT8量化占1字节，INT4量化占0.5字节71% similarVerifiedQ4量化将每个权重参数从16位压缩到4位，理论上可将模型体积缩小约75%71% similar
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