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Difference between Single Precision and Double Precision

Last Updated : 12 Jul, 2025
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In computer systems the floating-point numbers serve a very important purpose especially in scientific computing, computer graphics, and machine learning as it is used to represent real numbers. These floating-point numbers can be defined with different precision formats which are main single precision and double precision.

PrecisionBaseSignExponentSignificand
Single precision21823+1
Double precision211152+1

The two forms of Single and Double Precision really and truly differs by the number of bits that are used to represent these numbers and so varies the range and also the accuracy of the amount of numbers that can be found. Single precision requires 32 bits on a binary format while the double precision requires 64 bits. That is why it is critical to understand the difference in cases when the choice has to be made in favor of either speed or accuracy when it comes to computations.

Single Precision

Single Precision is a format proposed by IEEE for the representation of floating-point numbers. It occupies 32 bits in computer memory.

Advantages of Single Precision

  • Less Memory Usage: Thus single precision is favored because it requires only 32 bits, and is therefore more suitable for use in systems with restricted capacity.
  • Faster Computation: Certain operations performed in single precision may take lesser time than those performed in double precision because less number of bits are needed for processing in single precision. This is good for real time application like 3D graphic rendering and gaming.
  • Sufficient for Certain Applications: In a number of use cases, where the level of precision necessary is not extremely high, single precision is sufficient (for example, when it comes to graphics for video games or simulations, which do not have to be performed at a sufficiently high degree of accuracy, etc.).

Disadvantages of Single Precision

  • Limited Range: The smaller the bit size the range of values which can be used in a given application and therefore single precision is not applicable for use where very large/very small numbers are likely to be involved in the computation.
  • Lower Precision: Single precision formats can store only up to seven decimal digits with high accuracy, therefore, in scientific computations, precision is a problem.

Double Precision

Double Precision is also a format given by IEEE for the representation of the floating-point number. It occupies 64 bits in computer memory.

Advantages of Double Precision

  • Higher Accuracy: Double precision is far more accurate than the single precision mainly because it can express numbers with up to fifteen decimal digit.
  • Larger Range: Due to the extra bits for the exponent, double precision is capable of providing a lot more solutions in number ranges and this makes it ideal for most scientific or engineering related and any other computation that requires very large or very small values.
  • Better for Complex Calculations: Due to the high level of accuracy that it offers, double precision is useful when developing application that involves numeric such as simulations, statistics and machine learning.

Disadvantages of Double Precision

  • Higher Memory Consumption: Double precision thus needs double the bit space as compared to single precision (64 bits to 32 bits) and this may perhaps be a disadvantageous aspect when it comes to handling memory dominated systems.
  • Slower Computation: The chief disadvantage of operations in double precision is such operations are slower because there are more bits to get through, so it is not as ideal for real-time applications.
  • Overkill for Simple Tasks: However, for applications where the use of double precision is not very critical and may lead to wastage of computational resources.

Difference between Single and Double Precision

SINGLE PRECISIONDOUBLE PRECISION
In single precision, 32 bits are used to represent floating-point number.In double precision, 64 bits are used to represent floating-point number.
This format, also known as FP32, is suitable for calculations that won't be adversely affected by some approximation.This format, often known as FP64, is suitable to represent values that need a wider range or more exact computations.
It uses 8 bits for exponent.It uses 11 bits for exponent.
In single precision, 23 bits are used for mantissa.In double precision, 52 bits are used for mantissa.
Bias number is 127.Bias number is 1023.
Range of numbers in single precision : 2^(-126) to 2^(+127)Range of numbers in double precision : 2^(-1022) to 2^(+1023)
This is used where precision matters less.This is used where precision matters more.
It is used for wide representation.It is used for minimization of approximation.
It is used in simple programs like games.It is used in complex programs like scientific calculator.
This is called binary32.This is called binary64.
It requires fewer resources as compared to double precision.It provides more accurate results but at the cost of greater computational power, memory space, and data transfer.
It is less expensive.The cost incurred using this format does not always justify its use for every computation .

Conclusion

Which type to use, float single or float double, depends with the need of the program. Single precision is therefore faster and require less memory space this is advantageous in situations where the need to be very accurate is not as important as the speed at with information is processed. However, by using the double precision, one gets a higher degree of precision and a larger range of magnitude and therefore it is the better type of precision when doing numerical calculations in that involve scientific or engineering disciplines. Thus, their comparative analysis is critical to furthering the knowledge of the advantages and disadvantages of these two formats for computational processing.


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