Unverified50% confidenceFactExact time
A double-precision floating-point number can accurately represent approximately 15–17 significant decimal digits.
1
Sources
50%
Confidence
Long-term
Relevance
8/15/2026
First Seen
Sources
浮点数转字符串：你从未听说过的极速算法解析
Related Claims
UnverifiedFor double-precision floating-point numbers, one ULP near the value 1.0 is approximately 2^-52 ≈ 2.22×10^-16.70% similarUnverifiedfloat32的有效精度约为7位十进制数字，float64约为15位69% similarUnverifiedSingle-precision floating-point (float, 32-bit) has only 23 mantissa bits, and can precisely represent integers in the range of approximately ±2^24.67% 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% similarUnverifiedIEEE 754 双精度浮点数的指数偏移量为1023，实际指数范围为-1022到+102363% similar
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