Benchmark: JS BigInt big number performance v9

Script Preparation code:

var bigIntL = 1000000n
var bigIntM = 50n
var bigInt2 = 2n
var numberL = 1000000
var numberM = 50
var number2 = 2

Tests:

BigInt
a = bigIntL b = bigIntM c = a - b c = a % b c = a * b c = a + b c = bigInt2 ** b
Number
a = numberL b = numberM c = a - b c = a % b c = a * b c = a + b c = number2 ** b

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
BigInt
Number

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_3_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) FxiOS/136.2 Mobile/15E148 Safari/605.1.15

Browser/OS: Mobile Safari 18 on iOS 18.3.2

View result in a separate tab

Test name	Executions per second
BigInt	4513699.5 Ops/sec
Number	65226244.0 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):

LLMs can make mistakes. Check important info.

The benchmark described in the provided JSON compares the performance of JavaScript's `Number` type versus `BigInt` for handling large numeric operations. This comparison is significant due to the differences between how Standard Numbers and BigInts work in JavaScript, especially when dealing with very large integers.

### Options Compared

There are two main options being tested:

1. **BigInt**: This is a built-in object in JavaScript that provides a way to represent whole numbers larger than `2^53 - 1`, which is the limit of the `Number` type. In this benchmark, operations performed with `BigInt` involve:
   - Subtraction (`-`)
   - Modulus (`%`)
   - Multiplication (`*`)
   - Addition (`+`)
   - Exponentiation (`**`)

2. **Number**: This is the default numeric data type in JavaScript, which is a double-precision 64-bit binary format IEEE 754 value. Operations with `Number` in this benchmark are the same as those performed with `BigInt`.

### Pros and Cons

#### BigInt
**Pros:**
- Can represent extremely large integers without loss of precision, making it ideal for scenarios where overflow might be a concern (e.g., cryptography, high-precision calculations).
- Provides an intuitive approach for managing large integers, particularly for developers used to working with arbitrary-precision numbers in other languages.

**Cons:**
- Currently, BigInts cannot be mixed with `Number` types without explicit conversion, leading to potential challenges and limitations when integrating with existing codebases or libraries optimized for `Number`.
- Some arithmetic operations may be slower due to the overhead of handling larger data types and the complexity in their implementation.

#### Number
**Pros:**
- Offers better performance for many operations because of optimizations in JavaScript engines for floating-point arithmetic.
- Interoperates with a vast number of existing libraries and APIs that expect `Number`. Most mathematical operations are optimized for this type.

**Cons:**
- Limited to safe integer representation (up to `2^53 - 1`). Beyond this, precision errors may occur, which can be significant in calculations requiring high accuracy.
- Not suitable for very high-precision applications or financial calculations that might exceed the safe integer range.

### Other Considerations

1. **Test Results and Performance**: The benchmark results show that the `Number` type performs significantly better, achieving approximately 65 million executions per second, compared to about 4.5 million executions per second for `BigInt`. This performance difference is important to consider, especially for applications where processing speed is critical.

2. **Use Cases**: Depending on the application, choosing between `Number` and `BigInt` will depend on the required range of integer values and performance needs. In a performance-intensive application, where precise handling of small to moderately large integers is sufficient, `Number` would be preferable. Conversely, applications needing to handle large integers precisely without overflow will benefit from `BigInt`, despite the performance trade-off.

### Alternatives to BigInt and Number

- **Libraries**: There are JavaScript libraries (e.g., `big.js`, `decimal.js`, and `bignumber.js`) that can handle big numbers with higher precision or perform arithmetic operations efficiently. These libraries can often be tailored for specific use cases, offering additional functionality or performance optimization over built-in types, but they can also introduce larger payloads and dependencies into the project.

- **Typed Arrays**: For specific use cases involving numerical computations that require performance (e.g., game development, scientific applications), JavaScript's `Typed Arrays` (like `Int32Array`, `Float64Array`, etc.) can be used to handle numeric data more efficiently than general-purpose JavaScript arrays.

In conclusion, this benchmark highlights the critical performance differences between `Number` and `BigInt` in JavaScript. Developers should analyze the requirements of their applications carefully to choose the appropriate numeric type, keeping in mind both performance characteristics and the underlying mathematical needs.

Related benchmarks:

JS BigInt big number performance v9 (version: 1)

Compare Number vs BigInt for big numbers

Comparing performance of: BigInt vs Number

Created: one month ago by: Guest

Jump to the latest result

BigInt

Number

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one month ago):