Unverified50% confidenceFactExact time
For 32-bit integers exceeding 2²⁴, the mantissa precision of single-precision floating-point is insufficient to represent the value exactly, causing the exponent field to be underestimated.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
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Related Claims
UnverifiedSingle-precision floating-point (float, 32-bit) has only 23 mantissa bits, and can precisely represent integers in the range of approximately ±2^24.79% similarUnverifiedRegardless of the encoding scheme used, 4-bit precision can only distinguish 16 different numerical levels.72% similarUnverifiedDouble-precision floating-point (double, 64-bit) can precisely represent integers within the range of ±2^53, but still cannot cover the full range of 64-bit integer division.71% similarUnverifiedThe machine precision of double-precision floating-point numbers is approximately 2.22 × 10^-16.67% similarUnverifiedThe 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).67% similar
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