Code Bloat in Rust: The Simple Explanation

Ali Alachkar

4 min read

·

Oct 6, 2026

--

Listen

Share

In my previous article, I explained monomorphization in Rust.

The short version is:

Rust can create a specialized version of generic code for each type you use.

This is great for performance, but there is a small trade-off.

It can make your compiled program bigger.

This is called code bloat.

Press enter or click to view image in full size

What Is Code Bloat?

Code bloat simply means:

Your compiled program contains more code than it really needs.

For example, imagine you have:

fn process<T>(value: T) {
    // lots of code
}

And you use it with four different types:

process(user);
process(order);
process(product);
process(invoice);

Rust may generate specialized versions:

process::<User>
process::<Order>
process::<Product>
process::<Invoice>

Instead of one piece of machine code, you may now have several.

That’s the basic idea behind code bloat.

Why Does Rust Do This?

Because it can make the program faster.

Rust doesn’t want to sacrifice performance just to make generic programming convenient.

With monomorphization, the compiler knows the exact type and can optimize the code specifically for it.

So you get something like:

Generic code
     ↓
Specialized code
     ↓
Better optimization
     ↓
Potentially faster program

The trade-off is:

More specialized code
        ↓
Potentially larger binary

So it’s not a bug.

It’s a trade-off.

A Simple Example

Imagine this:

fn process<T: Processor>(value: T) {
    // 500 lines of code
}

And you use it with:

process(user);
process(order);
process(product);

Conceptually, Rust could generate:

process::<User>
process::<Order>
process::<Product>

If each version contains a lot of code, your final binary can become larger.

Of course, the compiler and LLVM perform many optimizations, so this doesn’t mean you literally get three identical copies of 500 lines.

Think of it as a potential source of duplicated machine code.

Does Code Bloat Matter?

Sometimes.

For a normal backend application, you probably won’t care.

A larger binary might not make any meaningful difference.

But binary size can matter more for:

• Embedded systems
• WebAssembly
• Serverless applications
• CLI tools
• Mobile applications
• Large applications

For example:

Small application
      ↓
5 MB binary

might become:

Same application
      ↓
10 MB binary

That may or may not matter depending on where you’re running it.

Code Bloat Can Also Affect Compilation

There’s another side effect.

More generated code means the compiler has more work to do.

Think about it like this:

1 generic function
       ↓
10 different types
       ↓
More specialized code
       ↓
More compiler work
       ↓
Potentially longer build time

So code bloat can affect:

Runtime:

Larger binary

and development:

Longer compilation

Should You Avoid Generics?

No.

This is probably the most important point.

Don’t see:

fn process<T: Trait>(value: T)

and immediately think:

“I should avoid this because it might create code bloat.”

Generics are one of Rust’s most useful features.

They give you:

• Type safety
• Reusable code
• Compile-time checking
• Excellent optimization opportunities

For most applications, just write clean generic code.

What About dyn Trait?

If binary size becomes a real problem, Rust gives you another option:

dynamic dispatch.

Instead of:

fn process<T: Processor>(value: T) {
    value.run();
}

you can write:

fn process(value: &dyn Processor) {
    value.run();
}

The difference is roughly:

Generics

T: Processor
     ↓
Monomorphization
     ↓
Multiple specialized versions

versus:

dyn Processor
     ↓
Dynamic dispatch
     ↓
One shared function

Dynamic dispatch can reduce duplicated code, but it introduces a small runtime cost and gives the compiler fewer opportunities to optimize.

So again, it’s a trade-off.

The Easy Mental Model

Think of monomorphization like making copies.

You have:

PROCESS

And you tell Rust:

Make one for User
Make one for Order
Make one for Product

You may end up with:

PROCESS<User>
PROCESS<Order>
PROCESS<Product>

More copies can mean:

More code
   ↓
Larger binary
   ↓
Potentially longer compilation

That’s code bloat.

Don’t Optimize Before You Need To

This is the main lesson.

You don’t need to replace every generic function with dyn Trait.

Instead:

Write clean Rust
      ↓
Build your application
      ↓
Measure
      ↓
Find actual problems
      ↓
Optimize if necessary

If you suspect your binary has too much generated code, tools such as cargo-bloat can help you find which functions are taking up the most space.

Don’t guess.

Measure.

Final Takeaway

If you remember only three things:

1. Monomorphization can generate specialized code

Generic code
     ↓
Different types
     ↓
Specialized versions

2. More generated code can cause code bloat

More code
   ↓
Larger binary
   ↓
Potentially longer compilation

3. Don’t avoid generics just because of this

Monomorphization exists because specialized code can be very fast.

The trade-off is simple:

Rust may do more work during compilation to give you better performance at runtime.

And if binary size ever becomes a real problem, measure it first, then consider alternatives such as dynamic dispatch.

Thanks for reading 🦀