Unlocking the Hidden Power of Your Laptop’s GPU

Most modern laptops come equipped with powerful GPUs that are often underutilized by their users.

Whether you are a software engineer running local LLMs, a data scientist processing large datasets, a developer compiling GPU-accelerated code, or an engineer running simulations, your system may not be using its full graphical and computational potential.

Many professionals invest in machines with dedicated GPUs such as NVIDIA, AMD, or similar, assuming applications will automatically use them. In reality, Windows often defaults to power-efficient integrated graphics unless explicitly instructed otherwise.

This means your expensive hardware could be sitting idle while your CPU struggles.

Step 1: Confirm Your System Has Multiple GPUs

Before changing any settings, verify your laptop actually has both integrated and dedicated GPUs.

Open:

Task Manager → Performance tab

On the left panel, you should see something like:

• GPU 0 – Integrated Graphics (Intel UHD)
• GPU 1 – Dedicated GPU (e.g., NVIDIA RTX 2000 Ada)

In the screenshot shared below it has:

• GPU 0 = Intel UHD Graphics (low-power)
• GPU 1 = NVIDIA RTX 2000 Ada (high-performance)

If you see two GPUs listed, your laptop supports GPU switching, as shown below.

Step 2: Check Whether Your Application Is Using the GPU

Even if you have a powerful GPU, your application may not be using it.

Open:

Task Manager → Details tab

Right-click on the column header → enable GPU and GPU Engine (if not already visible).

In the screenshot shared below it has:

• LM Studio.exe
• GPU column shows 71

This confirms the application is actively using the GPU.

If GPU usage shows:

• 0% consistently
• Or it only uses GPU 0 (integrated graphics)

Then it may not be using the dedicated GPU.

Why Windows Doesn’t Automatically Use Your Dedicated GPU

Windows prioritizes:

• Battery life
• Thermal efficiency
• Power savings

Unless an app is classified as a “high-performance” application (like many games), Windows may default to integrated graphics.

Developer tools, ML runtimes, simulation software, rendering engines, and scientific tools often don’t automatically trigger high-performance GPU usage.

That’s where manual configuration helps.

Step 3: Assign a Dedicated GPU to a Desktop Application

Navigate to:

Settings → System → Display → Graphics

Under Custom settings for applications, you will see:

• Add desktop app
• Add Microsoft Store app

Click Add desktop app

Browse to your application’s .exe file.

After adding the application:

• Click the app in the list.
• Select the available GPU associated with the "GPU preference" combobox.

All running instances of the application must be completely closed and then restarted for the changes to take effect.

How to Verify It’s Working

After enabling High Performance:

• Reopen Task Manager
• Go to the Details tab
• Confirm:
  • GPU usage increases when the app runs
  • GPU Engine shows GPU 1

You can also monitor the Performance tab and observe GPU 1 activity as shown below.

As a general recommendation, enable High Performance mode only for applications that are designed to use GPU acceleration, such as local LLM inference engines, CUDA-based tools, video editing tools, game engines, and scientific simulations.

Applications that are primarily CPU-bound, such as Microsoft Excel (even for large datasets), browsers, office applications, and lightweight utilities, will not benefit significantly from forcing the dedicated GPU.

In short, if the software explicitly supports GPU compute technologies like CUDA enabling High Performance mode can improve results; otherwise, it is best to leave the default settings unchanged.

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