Benchmark: bignumber.js vs. big.js vs. decimal.js (I) vs currencyjs

HTML Preparation code:

<!--script src="https://raw.githubusercontent.com/iriscouch/bigdecimal.js/v0.6.1/lib/bigdecimal.js"></script-->
<script src="https://cdnjs.cloudflare.com/ajax/libs/bignumber.js/9.0.1/bignumber.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/big.js/6.0.3/big.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/decimal.js/10.2.1/decimal.min.js"></script>
<script src="https://unpkg.com/currency.js/dist/currency.min.js"></script>
<!--script src="https://raw.githubusercontent.com/infusion/Fraction.js/v4.0.12/fraction.min.js"></script-->

Tests:

Native + toFixed
var a = 0.1; var b = 0.2; ((a + b) * b).toFixed(9);
decimal.js
var a = new Decimal("0.1"); var b = new Decimal("0.2"); a.plus(b).times(b).toString();
big.js
var a = new Big("0.1"); var b = new Big("0.2"); a.plus(b).mul(b).toString();
bignumber.js
var a = new BigNumber("0.1"); var b = new BigNumber("0.2"); a.plus(b).multipliedBy(b).toString();
currencyjs
var a = currency('0.1'); var b = currency('0.2'); a.add(b).multiply(b).value

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native + toFixed
decimal.js
big.js
bignumber.js
currencyjs

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gemma2:9b, generated one month ago):

LLMs can make mistakes. Check important info.

This benchmark tests the performance of different JavaScript libraries and the native `toFixed()` method for performing arithmetic operations on floating-point numbers.

**Options Compared:**

* **Native + toFixed:**  Uses the standard JavaScript `toFixed()` method to round the result of the calculation to nine decimal places. This is the simplest approach but can be prone to rounding errors due to how floating-point numbers are represented in computers.

* **decimal.js:** A library specifically designed for precise decimal arithmetic. It uses a fixed-precision representation to avoid rounding errors common with native JavaScript floats.

* **big.js:** Another library that handles arbitrary-precision decimal calculations, meaning it can perform operations on very large numbers without losing precision.

* **bignumber.js:**  Similar to `big.js`, this library supports arbitrary-precision arithmetic for both integers and decimals, offering high accuracy for complex calculations.

* **currency.js:** A library focused on representing and manipulating currency values. It handles formatting, conversions, and rounding specific to financial data.

**Pros and Cons:**

* **Native + toFixed:**
    * **Pros:** Simple, built-in, no external dependencies.
    * **Cons:** Prone to rounding errors, limited precision.

* **decimal.js, big.js, bignumber.js:**
    * **Pros:** High accuracy, arbitrary precision, suitable for complex calculations or scenarios requiring financial precision.
    * **Cons:**  Additional library dependency, potentially slower than native methods for simple operations.

* **currency.js:**
    * **Pros:** Tailored for currency handling, formatting, and conversions.
    * **Cons:** May be overkill if your needs are not strictly financial in nature.

**Other Considerations:**

* **Use Case:** The best choice depends on the specific application. For simple calculations with acceptable precision, native JavaScript might suffice. For high accuracy or financial applications, a dedicated library like `decimal.js`, `big.js`, or `bignumber.js` is recommended.
* **Performance Impact:** While these libraries offer accuracy, they often have a performance overhead compared to native methods.  Benchmarking your specific use case is crucial. 
* **Readability and Maintainability:** Consider the impact on code readability and maintainability when choosing a library.

**Summary:**

This benchmark highlights the trade-offs between simplicity and precision in JavaScript floating-point arithmetic. The results demonstrate that specialized libraries can significantly improve accuracy but may come with a performance cost.

Latest run results:

Run details: (Test run date: 15 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Native + toFixed	16719049.0 Ops/sec
decimal.js	1667072.4 Ops/sec
big.js	3017316.2 Ops/sec
bignumber.js	1582811.8 Ops/sec
currencyjs	570367.9 Ops/sec

Related benchmarks:

bignumber.js vs. big.js vs. decimal.js (I) vs currencyjs (version: 0)

- https://github.com/MikeMcl/bignumber.js/tree/v9.0.0 - https://github.com/MikeMcl/big.js/tree/v5.2.2 - https://github.com/MikeMcl/decimal.js/tree/v10.2.0

Comparing performance of: Native + toFixed vs decimal.js vs big.js vs bignumber.js vs currencyjs

Created: one year ago by: Guest

Jump to the latest result

Native + toFixed

decimal.js

big.js

bignumber.js

currencyjs

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gemma2:9b, generated one month ago):