Sharkbench

Benchmarking programming languages and web frameworks

Julia Computation Benchmark

About Julia

Paradigm

Functional, Object-Oriented, Imperative

Execution

JIT, AOT

Typing

Dynamic

Null Safety

NO

Memory Management

Garbage Collection

Julia is a high-level, high-performance dynamic programming language designed to be fast while remaining expressive and easy to use. It has execution speeds comparable to C and is particularly well-suited for scientific computing and data analysis. Julia is popular among researchers and data scientists due to its rich ecosystem of specialized packages.

Benchmarks

This benchmark tests how fast a programming language can perform mathematical computations without any I/O or memory allocation. We are using the Leibniz formula to approximate the value of PI.

OS: LinuxCPU: Intel Core Ultra 5 325Last Updated: 2026-10-14

Language	Time How long does it take to approximate PI? (lower is better)	Memory How much memory (RAM) does the program use? (lower is better)	Build Time Fetching dependencies + compiling, excluding SDK setup (lower is better)
Julia v1.10	1.00 s	356.7 MB	1.26 s

Popular languages

How does Julia compare to other languages?

Language	Time How long does it take to approximate PI? (lower is better, log scale)	Memory How much memory (RAM) does the program use? (lower is better)	Build Time Fetching dependencies + compiling, excluding SDK setup (lower is better)
Julia	1.00 s	356.7 MB	1.26 s
C (GCC)	1.00 s	2.2 MB	2.13 s
Rust	1.00 s	2.9 MB	4.12 s
Java (Temurin)	1.00 s	65.9 MB	14.84 s
C# (.NET)	1.16 s	34.8 MB	4.49 s
Go	1.36 s	3.8 MB	6.18 s
JavaScript (Node.js)	3.24 s	66.4 MB	1.09 s
Ruby	67.47 s	17.8 MB	1.29 s
Python	99.28 s	11.1 MB	1.28 s