Unverified50% confidenceFactExact time
float32的有效精度约为7位十进制数字，float64约为15位
1
Sources
50%
Confidence
Long-term
Relevance
8/5/2026
First Seen
Sources
Related Claims
UnverifiedSingle-precision floating-point (float, 32-bit) has only 23 mantissa bits, and can precisely represent integers in the range of approximately ±2^24.70% similarUnverifiedA double-precision floating-point number can accurately represent approximately 15–17 significant decimal digits.69% similarUnverifiedFP32 uses 32 binary bits to represent a number (1 sign bit, 8 exponent bits, 23 mantissa bits) and can accurately represent approximately 7 significant decimal digits.67% similarUnverifiedPython的浮点数遵循IEEE 754双精度浮点数标准，使用64位二进制来表示一个小数67% 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.65% similar
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