How Firefox Runs Natively on Apple M-Series Processors

This article explains the technical mechanics behind how the Mozilla Firefox web browser achieves native execution on Apple Silicon M-series processors using Apple's Universal Binary format. By packaging both Intel and ARM64 code into a single application bundle, Firefox allows the macOS operating system to automatically select and execute the native instruction set for M-series chips. Below is a straightforward breakdown of how the Universal Binary is constructed, how the operating system handles the execution, and how Firefox's internal engines are optimized for Apple's custom silicon.

The Universal 2 Binary Format

To support both legacy Intel-based Macs and modern Apple Silicon Macs without forcing users to download specific versions, Mozilla distributes Firefox as a Universal 2 Binary.

During the build process, Mozilla’s compilers translate the Firefox source code into two entirely separate sets of machine code:

  1. x86_64: The instruction set for Intel processors.
  2. ARM64 (AArch64): The instruction set for Apple M-series processors.

Once both versions are compiled, a macOS development tool merges these two executables into a single "fat" binary file (specifically, a multi-architecture Mach-O file). Despite containing code for two different processor architectures, this appears to the user as a single Firefox application icon.

How macOS Executes the Native Code

When you double-click the Firefox icon on a Mac with an M1, M2, or M3 processor, the macOS kernel reads the header of the Universal Binary file. This header acts as a directory, listing the different architectures supported by the application.

Recognizing that it is running on an M-series chip, macOS completely ignores the x86_64 Intel code path and loads only the ARM64 code into the system's memory. Because the ARM64 instructions match the native language of the M-series processor, the CPU can execute the code directly. This bypasses Rosetta 2, Apple's translation layer, eliminating the performance overhead and battery drain associated with real-time code translation.

Native JavaScript Compilation (SpiderMonkey)

Running the browser interface natively is only half the battle; a web browser must also compile and run code from the websites you visit. Firefox uses an engine called SpiderMonkey to process JavaScript.

To run natively on Apple Silicon, Mozilla engineered SpiderMonkey’s Just-In-Time (JIT) compiler to understand the ARM64 architecture. When you load a complex webpage, SpiderMonkey translates the website's JavaScript directly into native ARM64 machine code on the fly. It also utilizes Apple Silicon's hardware-enforced security features, such as Pointer Authentication and W^X (Write XOR Execute) memory protection, ensuring that dynamically generated web code runs both rapidly and securely on the M-series CPU cores.

Hardware Acceleration and Core Management

Firefox's native execution also relies heavily on how it interacts with the specific hardware layout of M-series chips:

  • CPU Core Scheduling: Apple Silicon uses a hybrid architectureconsisting of high-performance cores and high-efficiency cores. The native ARM64 build of Firefox communicates with macOS to route heavy tasks (like page rendering and video decoding) to the performance cores, while pushing background tasks (like tab unloading and telemetry) to the efficiency cores to save battery.
  • WebRender and the GPU: Firefox uses a graphics engine called WebRender, written in the Rust programming language. On M-series chips, this engine compiles natively to interface directly with Apple's Metal graphics API. Because Apple Silicon uses a Unified Memory Architecture—where the CPU and GPU share the same pool of RAM—Firefox can pass visual data from the processor to the graphics cores instantly without copying data across different memory pools.

By combining a dual-architecture file format with a fully rewritten ARM64 JavaScript engine and Metal-optimized graphics rendering, the Universal Binary of Firefox operates with maximum efficiency on Apple Silicon hardware.