Will WebAssembly Kill JavaScript? Let’s Find Out (+ Live Demo) 🚀

Source: Dev.to

TL;DR 🧠

A small live demo with WASM vs. JS benchmarks and the GitHub repo.

• JavaScript on its own is already very fast and totally fine for most tasks.
• When it comes to heavy computations, WASM has a big advantage, even without fancy optimizations like SIMD.

⚠️ I intentionally didn’t validate the inputs – be careful, it’s very easy to freeze your browser tab.

Demo:
Repo:

How do we even write WebAssembly code? 🤔

The basics

Code that gets compiled to WASM is usually written in low‑level languages such as:

• Rust
• Go
• C / C++

Why not Python or plain JavaScript?

WebAssembly is not native CPU machine code.
It’s a portable bytecode format that browsers later JIT‑compile to machine code – very similar to what they do with JavaScript.

The main problem with Python or JS isn’t “heavy compilers”, but:

• dynamic typing
• large runtimes
• garbage collection
• unpredictable memory models

WASM is designed around a simple, predictable execution and memory model, which fits languages like Rust or C++ much better. (Yes, WASM GC exists and is evolving, but it’s still far from mainstream in production.)

Why I used Rust 🦀

In the demo I used Rust, mostly because it has a near‑zero runtime and gives you explicit control over memory.

• It’s not that hard to set up, even on Windows (just install the Visual Studio toolchain).
• Rust is often described as “TypeScript on steroids” – very strict about types, no any.
• Concepts like ownership and borrowing help prevent many bugs.

If you want to dive deeper, dev.to alone has tons of great Rust articles.

Compiling to WASM

The compilation process is straightforward and can be integrated into CI/CD pipelines.
The repository includes the compiled files so you can inspect the actual WASM output and see how it’s used from JavaScript.

When should I use WASM and when is JavaScript better? ⚔️

You can verify everything yourself in the demo. The benchmark code is publicly available on GitHub, so you can confirm that no cheating is involved.

Reminder: input values are your responsibility – it’s easy to freeze a browser tab.

JavaScript is really fast 🏎️

WASM is insanely fast, but browser engine authors are not sleeping either. JIT compilation in engines like V8 or SpiderMonkey works extremely well.

If you’re writing a normal frontend app (simple CRUD, lots of DOM interactions), plain JavaScript can easily be faster overall, even with fairly heavy but straightforward computations.

Example: matrix multiplication

n × n matrix multiplication returning a single number (mod 1 000 000 007) is handled perfectly fine by JS and often appears “faster” than WASM.

The reason is the overhead of crossing the JS ↔ WASM boundary – the more often you cross it and the more data you copy, the more you erode any performance gains.

Where JS starts losing 💥

Things change with really heavy computations.

Example: factorial modulo

n! mod 1 000 000 007 makes JavaScript much slower than WASM. The absolute time is still low for this tiny example, but imagine:

• physics simulations
• numerical solvers
• large statistical models

JavaScript uses IEEE‑754 double‑precision numbers; for very large values it must switch to BigInt, which is slow. Rust, on the other hand, operates on u64 natively, creating a massive performance gap.

Results also differ by:

• browser
• JS engine
• hardware

On my machine the gap is smaller in Firefox than in Chrome.

What about image processing? 🖼️

WASM is often mentioned for image, video, and audio processing – and it can be amazing.

However, a very simple benchmark (applying a Gaussian blur to an image) showed JS completely destroying WASM because the entire Uint8Array had to be copied into WASM memory.

WASM only started winning when I built a full image‑processing pipeline:

• applied multiple filters in a row
• kept as much work as possible inside WASM

Lesson: “WASM is great for images” is true only when the operations are heavy enough. (Shared memory can reduce overhead but adds complexity.)

Even Gaussian blur, which processes millions of pixels, is handled surprisingly well by JS.

Bonus: WASM is not the only tool 🧰

Other web technologies can sometimes be perfect alternatives:

• Web Workers – offload heavy work to background threads.
• OffscreenCanvas – render graphics off the main thread.
• GPU solutions (WebGPU) – leverage the GPU for parallel workloads.

Choosing the right tool depends on the specific problem you’re trying to solve.