Double to Hex Converter
Convert a double-precision floating-point number into its exact IEEE 754 64-bit hexadecimal representation. Inspect the sign bit, exponent, fraction, raw binary pattern, bytes, and final 16-digit hexadecimal value directly in your browser.
What Is a Double to Hex Converter?
A Double to Hex Converter converts a double-precision floating-point number into the hexadecimal representation of its underlying 64-bit IEEE 754 binary pattern. Instead of converting the numerical value as if it were an ordinary integer, the converter exposes the exact bits used to store that floating-point value in memory.
This distinction matters because a double is not stored as a simple base-10 or base-16 number. IEEE 754 binary64 divides the 64 available bits into three fields: a one-bit sign, an eleven-bit exponent, and a fifty-two-bit fraction. Together these fields describe normal values, subnormal numbers, positive and negative zero, infinity, and NaN.
BinaryCon’s converter performs the conversion locally in the browser using an 8-byte binary buffer. The resulting bytes are then displayed as sixteen hexadecimal digits, allowing developers to inspect the same bit-level representation used by common programming languages, processors, binary files, network protocols, debuggers, and data serialization formats.
Enter a decimal double
Type a floating-point value such as 12.5, -2.5, 0.1, 3.141592653589793, or a value written using scientific notation.
Encode to binary64
The number is stored as an IEEE 754 double using one sign bit, eleven exponent bits, and fifty-two fraction bits.
Read the hexadecimal
The complete 64-bit pattern is grouped into sixteen hexadecimal digits so the raw representation is easier to inspect or copy.
IEEE 754 Double-Precision Format
IEEE 754 double precision is commonly called binary64. Every normal double-precision number occupies 64 bits, equal to eight bytes or sixteen hexadecimal digits. Those bits are divided into three logical fields.
Sign bit
The first bit controls the sign. A sign bit of 0 represents a positive value, while a sign bit of 1 represents a negative value. IEEE 754 also supports both positive zero and negative zero, meaning the sign bit can remain significant even when the mathematical magnitude is zero.
Exponent field
The next eleven bits store a biased exponent. For ordinary normalized values, the stored exponent is related to the real binary exponent by an exponent bias of 1023. Special exponent patterns are reserved for subnormal values, infinity, and NaN.
Fraction field
The remaining fifty-two bits hold the fractional portion of the significand. Normal IEEE 754 numbers also use an implicit leading binary 1, giving approximately 53 bits of significand precision even though only 52 fraction bits are physically stored.
Double to Hex Conversion Examples
These examples show the important difference between formatting a number in hexadecimal and viewing the hexadecimal representation of the number’s floating-point bits.
Common Double Values and Their Hex Representations
The reference table below contains several useful IEEE 754 binary64 patterns. These values are especially useful when checking encoders, debugging binary data, writing unit tests, or verifying language and protocol implementations.
| Double value | IEEE 754 hexadecimal | Meaning |
|---|---|---|
| 0 | 0000000000000000 |
Positive zero |
| -0 | 8000000000000000 |
Negative zero |
| 1 | 3FF0000000000000 |
Positive one |
| -1 | BFF0000000000000 |
Negative one |
| 2 | 4000000000000000 |
Positive two |
| 2.5 | 4004000000000000 |
Exact binary fraction |
| 12.5 | 4029000000000000 |
Example decimal value |
| 0.5 | 3FE0000000000000 |
Exact one-half |
| 0.1 | 3FB999999999999A |
Rounded binary approximation |
| π | 400921FB54442D18 |
Nearest binary64 representation of π |
| +Infinity | 7FF0000000000000 |
Positive infinity |
| -Infinity | FFF0000000000000 |
Negative infinity |
How Is a Double Converted to Hexadecimal?
The conversion process is easier to understand when separated into representation and formatting. A decimal floating-point value is first encoded into an IEEE 754 binary64 bit pattern. Only after that pattern exists are the bits grouped into hexadecimal digits.
Step 1: Determine the sign
A positive input receives a sign bit of 0. A negative input receives a sign bit of 1. The magnitude of the number is encoded by the remaining exponent and fraction fields.
Step 2: Express the magnitude in normalized binary form
For a normal finite value, the binary representation is conceptually normalized into a form similar to 1.fraction × 2exponent. The real exponent is then stored using the binary64 bias of 1023.
Step 3: Encode the fraction
Bits after the leading normalized 1 are placed into the 52-bit fraction field. If the exact mathematical value requires more precision than the format provides, IEEE 754 rounding rules determine the nearest stored representation.
Step 4: Combine all 64 bits
Sign, exponent, and fraction bits are concatenated into one continuous 64-bit sequence.
Step 5: Convert each four-bit group to hex
Four binary bits correspond to one hexadecimal digit. Since a double contains 64 bits, the complete raw representation always occupies sixteen hexadecimal digits.
Why 0.1 Has a Surprising Hex Value
One of the most useful demonstrations of floating-point representation is decimal 0.1. People often expect a computer to store the value exactly as typed, but 0.1 has no finite representation in base 2. Its binary fractional expansion repeats indefinitely.
A binary64 implementation therefore stores the nearest representable
double. For ordinary IEEE 754 double precision, the resulting raw
hexadecimal pattern is 3FB999999999999A.
This behavior explains many familiar floating-point effects in programming, such as why repeated decimal arithmetic can produce tiny rounding differences. The Double to Hex Converter makes those internal representations visible instead of hiding them behind decimal output.
Double Precision Data Reference
These properties are useful when interpreting hexadecimal floating-point data from programs, files, protocols, embedded systems, and memory dumps.
| Property | Binary64 value | Explanation |
|---|---|---|
| Total storage | 64 bits | Eight bytes per double |
| Sign field | 1 bit | Controls positive or negative sign |
| Exponent field | 11 bits | Stores the biased binary exponent |
| Fraction field | 52 bits | Stores significand fraction bits |
| Exponent bias | 1023 | Used when encoding normal exponents |
| Hex width | 16 digits | Each hex digit represents four bits |
| Approximate decimal precision | 15–17 significant digits | Typical decimal round-trip precision range |
Double Hex vs Numeric Hex Conversion
A common mistake is confusing the hexadecimal form of an integer with the hexadecimal encoding of a floating-point number. These are two different operations.
If the integer value 12 is converted numerically to hexadecimal, the answer is C. But if 12.0 is stored as an IEEE 754 double and its raw memory representation is displayed in hexadecimal, the result is 4028000000000000.
The Double to Hex Converter performs the second operation. It exposes the binary64 storage representation rather than merely changing the printed radix of the number.
Where Double-to-Hex Conversion Is Useful
Raw double representations appear in many areas of software engineering and computer science. Being able to inspect the hexadecimal encoding can make otherwise invisible floating-point behavior much easier to diagnose.
Binary file analysis
Compare expected double values with eight-byte fields found inside scientific files, custom data formats, or binary exports.
Protocol debugging
Verify floating-point payloads sent through network protocols, industrial interfaces, device messages, or serialized structures.
Programming diagnostics
Inspect the exact representation behind unexpected rounding, equality comparisons, numerical edge cases, and test failures.
Reverse engineering
Identify possible 64-bit floating-point fields in raw memory, packet captures, firmware data, or undocumented structures.
Education
Study sign, exponent, fraction, normalization, rounding, infinity, NaN, and subnormal values with visible bit patterns.
Test vector creation
Generate known hexadecimal values for unit tests, parsers, encoders, decoders, and cross-language compatibility checks.
Special IEEE 754 Double Values
Not every 64-bit floating-point pattern represents an ordinary finite number. IEEE 754 reserves certain exponent and fraction combinations for special numerical states.
Positive and negative zero
Binary64 has two zero representations. Positive zero has all bits clear, while negative zero sets only the sign bit. Most arithmetic treats them similarly, but their bit patterns are different.
Infinity
Infinity uses an exponent containing all ones and a zero fraction. The sign bit determines positive or negative infinity.
NaN
NaN means “Not a Number.” It uses an all-ones exponent together with a nonzero fraction. Multiple NaN bit patterns are possible, so a system does not necessarily have only one valid NaN hexadecimal representation.
Subnormal numbers
When the exponent field is zero but the fraction is nonzero, the value is subnormal. Subnormal numbers allow binary64 to represent magnitudes closer to zero than the smallest normal value, though with reduced effective precision.
Endianness and Double Hexadecimal Bytes
The sixteen-digit hexadecimal value displayed by this calculator is a conventional big-endian presentation of the 64-bit IEEE 754 bit pattern: the most significant byte is shown first.
Actual byte order in memory can depend on the computer architecture or binary protocol. On a little-endian system, the eight bytes may appear in reverse order when viewed directly in memory.
For example, the canonical IEEE 754 hexadecimal representation of
12.5 is 4029000000000000. Its big-endian byte sequence is
40 29 00 00 00 00 00 00. A little-endian memory dump may
instead show those bytes as 00 00 00 00 00 00 29 40.
Common Double-to-Hex Conversion Mistakes
Incorrect results are often caused by interpretation rather than the floating-point encoding itself. These are the issues worth checking first.
Using float32 instead of float64
A standard single-precision float uses only 32 bits and produces eight hexadecimal digits. A double uses 64 bits and normally produces sixteen hexadecimal digits. The two representations are not interchangeable.
Converting the integer part only
Hex formatting functions designed for integers may discard or reject fractional input. They do not expose the IEEE 754 representation.
Ignoring endianness
Reversed byte order can make a correct floating-point value appear completely different in a raw binary file or memory dump.
Expecting every decimal fraction to be exact
Values such as 0.5 are exactly representable in binary, while values such as 0.1 are not. A hexadecimal result that looks unusual can therefore be completely correct.
Double to Hex Converter FAQ
These answers cover the most common questions about IEEE 754 double-precision hexadecimal conversion.