Most performance guides tell you to write code that looks like it belongs in 1985. They're wrong. You don't need to sacrifice clean architecture just to hit 120 FPS. Here’s the real-world guide to Swift optimization that actually respects your teammates.

Stop Writing Code That Fights the Compiler

Look, we’ve all been there. You’re staring at a scroll view that stutters like a broken record, and your first instinct is to reach for some obscure micro-optimization you saw on a forum from 2017. Don’t do it. Most of the time, Swift isn’t slow your architecture is just making the compiler work twice as hard for no reason.

The biggest mistake I see? Devs treating Swift like it’s Java or Objective-C. Swift is a different beast. It loves static dispatch. It thrives on value types. When you try to force dynamic, flexible patterns where they aren’t needed, you’re basically putting lead weights on your app's feet. Let’s talk about how to fix that without turning your codebase into a pile of unreadable spaghetti.

The "Final" Touch: Why Visibility Matters

If you aren’t using final and private, you’re leaving money on the table. Every time you define a class or a method without these keywords, the compiler has to assume that someone, somewhere, might try to override it later. This forces the app to use Dynamic Dispatch, which means it has to look up the method at runtime in a "vtable." It’s a tiny delay, sure. But multiply that by 10,000 calls? It adds up.

The Fix is Dead Simple:

1. Mark classes as final by default. If you aren't inheriting from it, lock it down.
2. Use private and fileprivate. When the compiler knows a property won't be accessed outside a file, it can inline the code. It literally replaces the function call with the actual logic. No jump, no lookup, just raw speed.

Value Types are Your Best Friend (Mostly)

I saw a project once where every single data model was a class. The memory footprint was a nightmare. The app spent more time managing Reference Counting (ARC) than actually rendering pixels.

Classes are heavy. They live on the heap. They require thread-safe reference counting. Structs? They live on the stack. They’re "copied" (conceptually), but Swift is smart enough to use Copy-on-Write (CoW) to make sure it only actually copies data when it absolutely has to.

Pro Tip: If your data model is just a "bag of data" for a view, make it a struct. Your CPU will thank you because it doesn't have to track who owns what. It just uses the data and moves on.

The Silent Lag: Collections and Lazy Loading

We’ve all written that one filter().map().reduce() chain that looks beautiful but runs like a tractor. The problem? Every one of those functions creates a brand-new array in memory.

If you’re dealing with a massive dataset say, 5,000 items from a JSON response don’t chain these directly. Use .lazy.

swift

// Don't do this with 10k items
let results = bigArray.filter { $0.isActive }.map { $0.name }

// Do this instead
let results = bigArray.lazy.filter { $0.isActive }.map { $0.name }

By adding .lazy, Swift doesn't create the intermediate arrays. It only computes the transformation when you actually try to access an element. It’s a massive win for memory pressure.

A 2 A.M. War Story: The Lazy Property Trap

Here’s a mistake I made that I’ll never forget. I once used a lazy var to initialize a heavy database manager. I thought I was being clever by delaying the work. But I forgot that lazy isn't thread-safe by default.

During a high-traffic sync, two threads hit that property at the same time. The database initialized twice, corrupted the local cache, and crashed the app for about 15% of our users.

The Lesson: Performance isn’t just about speed; it’s about predictability. If you need a heavy object, sometimes it’s better to initialize it explicitly on a background queue rather than hiding it behind a "clever" lazy property that might blow up in a multi-threaded environment.

Choosing the Right Tool for the Job

Not all optimizations are equal. Here is a quick breakdown of where to focus your energy based on my experience scaling apps to millions of users.

The Verdict

Performance optimization in Swift isn't about some secret "Turbo" button. It’s about getting out of the compiler's way. If you write code that is clear, explicit about its intent (using final), and prefers value types over reference types, the compiler will do the heavy lifting for you.

Don't optimize early. Use Instruments to find the actual bottlenecks. But when you do find them, fix them with patterns that make your code more robust, not more confusing.