Performance Comparison of Multiple Programming Languages on a 1 Billion Nested Loop

The article presents a benchmark comparing the execution time of a 1 billion‑iteration nested loop across dozens of programming languages on an M3 MacBook Pro (16 GB RAM), using /usr/bin/time and hyperfine.

Results show compiled languages such as C, Rust and Java achieve the best performance (~0.5 s), while interpreted languages like Python and Ruby are much slower (Python 74.42 s, Ruby 68.96 s). The Fibonacci calculation also ranks C and Rust fastest (0.40 s and 0.41 s), with Python and R at the bottom.

Additional tests with more languages (Zig, Swift, Fortran, etc.) confirm that Zig, Rust and C remain the fastest, all around 0.5 s, and that Python 3.13 improves to 31.589 s. R remains the slowest at 72.643 s.

The testing environment details the compiler and interpreter versions for each language (e.g., Apple clang 16.0.0, Rust cargo 1.82.0, Python 3.13, etc.).

Instructions are provided to clone the benchmark repository, compile, run, and clean the tests:

<code>git clone https://github.com/bddicken/languages</code>

<code>cd loops</code>

<code>../compile.sh</code>

<code>../run.sh</code>

<code>../clean.sh</code>

Sample output demonstrates the timing format for Zig, C, and Rust benchmarks.

The article also includes promotional material encouraging readers to follow the public account and scan a QR code to receive free Python learning resources.