Parallels Processors: How Virtual CPUs Work on Apple Silicon Macs

You want to run a Windows virtual machine (VM) on your Mac, so you launch Parallels Desktop. Everything boots up, and you see a prompt about processors, but you’re not sure what it means, or how many you should allocate.

This guide is designed to help you understand exactly that: how Parallels processors work, how Parallels Desktop uses Apple Silicon CPU resources, what you need to know about different M-series chips, and most importantly, how to choose the right settings for your desired performance.

What we mean by Parallels processors in a virtual machine

What do you need to know about Parallels processors? Processors refer to virtual CPUs assigned to a virtual machine; they're not new physical cores added to your Mac. Think of it as the slice of your Mac’s existing CPU resources allotted to the VM, which powers Parallels Desktop to run full operating systems locally on your Mac.

With Parallels Desktop, users control how much capacity the VM can use. But macOS still manages the actual hardware cores, especially on Apple silicon, where performance and efficiency cores are dynamically scheduled. Parallels works within that system, requesting CPU time for the VM while macOS decides how to distribute the workload.

On Apple silicon Macs, Parallels installs and runs Windows 11 on ARM inside that virtual machine. For most modern applications, Windows runs natively on ARM. When you use older x86 or x64 Windows apps, Windows 11 on ARM includes built-in emulation to run them.

Why Apple Silicon changes virtual machine performance

Virtualization is a fast-growing industry; the market has grown by the billions in recent years, and there have been many recent advancements in this space. Modern Macs (such as those with M1, M2, M3, M4, or M5 chips) use Apple Silicon chips, which fundamentally change how well local VMs run.

On older Intel-based Macs, virtualization worked but often came with trade-offs, such as noticeable slowdowns. The CPU architecture wasn’t designed for the sustained, parallel workloads that modern virtualization demands.

But with Apple Silicon, virtualization feels like a natural extension of your computer.

That’s because these chips were designed with:

• High-performance cores for demanding tasks.
• High-efficiency cores for background work.
• Built-in hardware virtualization support.

From Intel Macs to Apple Silicon, one of the biggest architectural shifts is unified memory.

On Apple silicon, the CPU, GPU, and system components share a single memory pool. This improves performance for computing and graphics tasks because the CPU and GPU don’t need to transfer data between them; they operate as one.

Across the M-series lineup, each generation improves performance, efficiency, and scheduling behavior. M5 refined what M4 did well, which improved what M3 introduced. Apple Silicon makes local virtualization feel stable, fast, and cohesive.

How Parallels Desktop uses Apple Silicon for virtual machines

When you configure Parallels processors and memory, you’re controlling how much of your Mac’s hardware your virtual machine can use. To find these settings, choose Actions > Configure > Hardware, then click CPU & Memory.

If you're using Windows 10 or later, Parallels Desktop automatically allocates the required number of CPUs and memory to the virtual machine, so you get optimal performance and a good experience. But you can tailor that choice based on your desired experience and workload.

Keep in mind, you need to maintain a balance:

• If you assign too few processors, Windows apps may feel slow during heavy tasks like builds, data processing, or large Excel models.
• If you assign too many, macOS can feel laggy, especially if you’re running browsers, design tools, or video calls alongside your VM.
• The same is true for memory. On Apple silicon Macs, unified memory is shared across the entire system. Allocating most of it to the VM can cause memory pressure on macOS, reducing responsiveness across the system.

As we touched on earlier, on Apple silicon Macs, Parallels Desktop is optimized for Apple Silicon and Windows 11 on ARM. Many modern Windows apps run directly on ARM. Older x86 and x64 applications run through Microsoft’s built-in emulation layer within Windows.

In everyday use, this translates to:

• Fast boot times.
• Responsive UI.
• Stable performance for business apps, dev tools, and many creative workflows.
• Support for thousands of Windows applications used by Mac-first professionals.

You may notice limits with:

• Extremely GPU-heavy 3D rendering compared to a dedicated Windows workstation.
• Workloads that continuously demand a large amount of system memory.

Overall, it’s best to think of this setup as a strong all-around performer that handles most creative and professional work smoothly, with the main trade-offs appearing only in the most extreme GPU-bound rendering tasks and in projects that keep very large amounts of data in memory for long stretches.

CPU and memory allocation options

Not every Windows workflow needs the same processor and memory settings. The right configuration depends on both your Mac’s specs and what you’re actually doing in the VM.

As a quick rule of thumb:

• Processor-heavy workloads might benefit from more vCPUs.
• Memory-heavy workloads might benefit from more RAM.
• Most everyday work benefits more from balance than from maxing either setting.

Here are some things to keep in mind:

• If you're using Windows 10 or later, Parallels Desktop automatically allocates the required number of CPUs and memory to the virtual machine, so you get optimal performance and a good experience.
• It is recommended that you use the default settings.
• If you are not satisfied with the virtual machine's performance, you can manually specify the amount of CPU and memory your virtual machine can consume.
• Virtual machines created and run in Parallels Desktop for Mac Standard Edition are limited to 4 vCPU cores and 8GB of vRAM.
• For Pro and Business/Enterprise Editions, the limitations are:
  • Up to 32 vCPU cores for Intel Macs and up to 18 vCPU cores for Apple silicon Macs (maximum tested number).
  • Up to 128GB of RAM.

Keep in mind, more is not always better. If the recommended settings are not sufficient, try adding more memory and/or increasing the number of CPUs. If the virtual machine becomes faster, it's ok. If not, try to further adjust the allocations.

How to choose the right processor setting

Choosing the right Parallels processor settings depends on your workload and goals. Here are some tips to keep in mind.

1. Start conservative

   With the recommended settings, run your workload, open apps you normally use, and execute a workflow. If everything feels smooth, stop there.

2. Increase gradually

   If your workflow consistently pushes CPU usage high, such as long compiles or sustained data processing, add some values and test again.

   Remember, adding processors increases scheduling overhead. Your Mac still has a fixed number of physical cores, and macOS must coordinate work between the VM, background system processes, your open Mac apps, and system services. Too many processors can lead to diminishing returns.

3. Always leave headroom for macOS

Your Mac is still your primary computer. If Windows gets all the CPU attention, your browser, video calls, and design tools will compete for what’s left.

Maintaining headroom ensures smooth multitasking, stable video calls, and a more predictable battery life.

Note: Higher-tier Apple Silicon Macs allow more flexibility, giving you more room to scale for heavier workloads or more simultaneous VMs.

Parallels Desktop compared to other ways to run Windows on a Mac

If your goal is to run Windows locally on your Mac with full performance, offline access, and tight macOS integration, Parallels Desktop is purpose-built for that.

In general, there are several ways to solve the Windows-on-Mac problem:

• Remote desktop or cloud-hosted Windows PCs.
• Compatibility layers that attempt to run individual Windows apps without Windows itself.
• Dual-boot setups on older hardware.

Each approach solves a different problem. But if you specifically want to run Windows apps directly on your Mac, side by side with macOS, Parallels Desktop focuses on compatibility, performance, and ease of use.

Getting the most from Parallels processors on M3

In Parallels, processors control virtual CPU access, not raw hardware cores. You’re deciding how much virtual CPU access your Windows virtual machine can use at any given time.

And on any modern Apple silicon system, that decision will be based on your workload and striking the right balance between performance and macOS responsiveness.

If you want to go deeper, review the official Parallels Desktop documentation for guidance on CPU and memory configuration.

Or better yet, start a free trial and test your real workflow firsthand.