Unverified50% confidenceFactExact time
Different quantization levels produce different numerical ranges (for example, the 8-bit quantization range is [-128,127] and the 4-bit range is [-8,7]); if unified to the same prime p, the values of low-precision clients may be amplified or the values of high-precision clients may overflow, breaking correctness.
1
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50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
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Related Claims
Unverified对于7B至13B参数级别的模型，4-bit量化后的输出质量与全精度版本差异很小76% similarVerifiedThe 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).72% similarUnverifiedRegardless of the encoding scheme used, 4-bit precision can only distinguish 16 different numerical levels.70% similarUnverifiedMixed-precision quantization applies aggressive low precision such as INT4 to backbone networks that have large parameter counts but are not precision-sensitive, while retaining INT8 or FP16 for precision-sensitive components such as text encoders and QKV projections.67% similarUnverified4-bit量化只能表示16个离散值，1-bit只有2个，三元量化（-1/0/+1）只有3个可能值67% similar
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