Benchmark: number vs bigint add

Tests:

number
for (let i = 10000; i--;) { 1 + i }
bigint
for (let i = 10000n; i--;) { 1n + i }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
number
bigint

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/133.0.0.0 Safari/537.36 Edg/133.0.0.0

Browser/OS: Chrome 133 on Windows

View result in a separate tab

Test name	Executions per second
number	196490.1 Ops/sec
bigint	2499.9 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark, specifically testing the performance of adding numbers with either traditional 32-bit integers (numbers) or large 64-bit integers (bigint).

**Options Compared**

Two options are being compared:

1. **Number**: Traditional 32-bit integer addition.
2. **Bigint**: Large 64-bit integer addition.

These two approaches differ in their underlying data types and behavior.

**Pros and Cons of Each Approach:**

### Number

Pros:

* Typically faster and more efficient due to lower memory overhead and optimized JavaScript engine implementation for small integers.
* Usually sufficient for most numerical computations where the result doesn't exceed a reasonable size (e.g., small integers, floating-point numbers).

Cons:

* May overflow or produce unexpected results when dealing with very large numbers that exceed the maximum value of 32-bit signed integers (usually around ±2^31-1).
* Limited precision and accuracy for certain calculations involving extremely large or small numbers.

### Bigint

Pros:

* Can handle arbitrarily large numbers without worrying about overflow, making it suitable for applications requiring numerical computations with extremely large values.
* Provides more accurate results for certain calculations involving very large or small numbers.

Cons:

* Typically slower than using numbers due to increased memory overhead and potentially less optimized JavaScript engine implementation for large integers.
* May require careful handling of special cases, such as rounding errors or precision issues, depending on the specific use case.

**Library**

In this benchmark, no external library is explicitly mentioned. However, it's essential to note that some JavaScript engines or libraries might implement additional optimizations or features that could affect performance in certain scenarios (e.g., SIMD instructions for parallelization).

**Special JS Feature/Syntax**

This benchmark does not specifically utilize any special JavaScript features or syntax beyond the traditional `let`, `for` loops, and arithmetic operators. The focus is on comparing the performance of simple addition operations with numbers versus BigInt.

**Other Alternatives**

If you were to modify this benchmark to explore different aspects, some possible alternatives could include:

* **Number vs BigInt multiplication**: Compare the performance of multiplying numbers versus BigInt.
* **Array operations**: Test the performance of array-related methods (e.g., `push`, `splice`, `map`) with both traditional arrays and large arrays.
* **Object-oriented programming**: Benchmark the performance of object-related methods (e.g., property access, method calls) with different data types and scenarios.

By exploring these alternative benchmarks, you can gain a deeper understanding of JavaScript's strengths and weaknesses in various performance-critical scenarios.

Related benchmarks:

number vs bigint add (version: 0)

Comparing performance of: number vs bigint

Created: 3 years ago by: Guest

Jump to the latest result

number

bigint

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):