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On Windows, start with Task Manager → Performance → GPU and watch the memory graphs while your workload is running. Choose the entry for the GPU the workload actually uses. For more detail, NVIDIA users can check nvidia-smi; Intel integrated-graphics users should interpret Windows memory figures as system-memory sharing, not necessarily physical VRAM. A high reading alone does not prove a bottleneck: look for sustained pressure near the available local-memory budget alongside repeatable errors, instability, or performance changes.
Choose a monitor that matches your GPU and operating system
| Monitor | What it helps you see | Important limitation |
|---|---|---|
| Windows Task Manager | GPU activity and memory graphs for the selected adapter. AMD documents GPU monitoring here for Windows 10 Fall Creators Update and later, though labels and layout vary by Windows release. AMD support guidance. | Confirm that you selected the adapter used by the workload. The graphs do not make every kind of graphics memory equivalent. |
nvidia-smi |
NVIDIA device information, including framebuffer total, reserved, used, and free values where supported. NVIDIA documents it for supported driver platforms. NVIDIA SMI documentation. | On Windows in WDDM mode, its per-process GPU-memory field is unavailable because the Windows kernel-mode driver manages that memory. NVIDIA SMI documentation. |
| Intel DxDiag | Reported dedicated memory for an Intel graphics adapter: open DxDiag, then Display Devices and inspect Dedicated Memory. Intel DxDiag guidance. | For integrated Intel graphics, the number is not necessarily a separate bank of physical VRAM; interpret it alongside shared system memory. Intel graphics memory FAQ. |
| AMD Software: Adrenalin Edition | AMD describes performance metrics, including GPU and memory usage, in its software. AMD support guidance. | Availability and layout depend on the software installation and supported hardware. |
Check memory use on Windows
Task Manager for a live overview
- Start the application or game whose memory use you want to inspect.
- Open Task Manager and select Performance, then choose the relevant GPU entry.
- Watch the memory graphs while reproducing the workload. If the computer has multiple adapters, verify which GPU the application is using before interpreting the figures.
AMD documents Task Manager GPU monitoring for Windows 10 Fall Creators Update and later; the exact interface can differ between Windows releases. AMD’s guidance also describes viewing PC performance metrics in Adrenalin software, when available for the installed system.
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Intel integrated graphics: check DxDiag, then account for shared memory
For the reported dedicated-memory figure, press Windows key + R, enter dxdiag, open the Display or Display Devices information, and inspect Dedicated Memory. Intel documents this check in its DxDiag instructions. Menu wording may vary.
That number needs context. Intel integrated processor graphics use system memory rather than a separate graphics-memory bank. Windows’ Shared System Memory figure is the limit the operating system may allow graphics to use, not an amount permanently reserved from the start. Intel also says its driver may report 128 MB of fictitious dedicated video memory for compatibility with applications that do not understand unified memory. This is a compatibility report, not a measurement of a physical VRAM bank. Intel graphics memory FAQ.
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NVIDIA: use nvidia-smi for device-level readings
Open a terminal or Command Prompt where the NVIDIA utility is available and run:
nvidia-smiLook at the GPU’s memory figures for total, reserved, used, and free framebuffer memory. The exact metrics available depend on the GPU and platform. On Windows using WDDM, do not treat the per-process GPU-memory column as a reliable process breakdown: NVIDIA marks that value unavailable in this mode because Windows’ kernel-mode driver manages the memory. NVIDIA SMI documentation.
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Check NVIDIA memory use on Linux or in a virtual machine
On supported NVIDIA Linux driver installations, nvidia-smi can report framebuffer memory and utilization metrics where the GPU and platform support them. Unsupported metrics may be omitted or shown as a dash; that does not mean the value is zero. For virtualized systems, results depend on where the tool runs: a guest VM’s view should not be assumed to represent all memory on the physical GPU. NVIDIA describes supported monitoring contexts in its SMI documentation and vGPU guide.
There is no single AMD Linux graphical-monitoring path established here for every distribution, driver stack, and GPU generation. Check the documentation for your specific setup rather than assuming one command or application applies universally.
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Read the number correctly: local VRAM, system memory, and accounting
Identify the memory pool before comparing numbers
A device-level framebuffer figure, a per-process figure, a local-memory segment, and shared system memory describe different things. NVIDIA documents per-process GPU memory as framebuffer memory on discrete GPUs or system memory on integrated GPUs; in Windows WDDM mode the per-process value is unavailable. NVIDIA SMI documentation. For Intel integrated graphics, shared system memory is system RAM that graphics may use, not dedicated physical VRAM.
Reported totals and post-exit values can be imperfect
NVIDIA says reported framebuffer totals can be affected by ECC and internal reservations, and accounting accuracy on GPUs managed as OS NUMA nodes depends on the operating system. It also notes that allocated pages may remain after a process ends to improve performance, while operating-system memory pressure can affect reporting. Therefore, a device total or a reading that remains after an application closes is not by itself proof of a leak or a workload bottleneck. NVIDIA SMI documentation.
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On certain Ryzen AI 300-series and later platforms, AMD’s Variable Graphics Memory feature can reallocate system RAM to integrated graphics through a BIOS setting. AMD distinguishes this dedicated allocation from shared memory; RAM assigned this way is no longer available to the CPU and system. This is a platform-specific allocation feature, not a general method for adding physical VRAM to any GPU. AMD Variable Graphics Memory information.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesDetermine whether VRAM is actually the bottleneck
- Record what the counter represents. Note the GPU, operating system, driver mode if relevant, workload, and whether the figure is device-level framebuffer memory, per-process memory, or shared system memory.
- Measure during the problem. Watch the counter while reproducing the slowdown or error. An idle reading or a value taken only after the application exits may not describe the workload’s peak use.
- Look for a repeatable combination of signs. Near-capacity memory use matters most when it occurs alongside workload-specific errors, instability, or a performance change that can be reproduced.
- Check other possible limits. Compare memory readings with GPU utilization and other system indicators. A slowdown alone does not identify VRAM as the cause; a workload may be limited elsewhere.
- Test a lower-memory workload if practical. Reduce memory-intensive settings or assets and see whether the same symptom changes. If evidence points to a genuine local-memory constraint, choose any hardware change based on the specific application and measured workload.
There is no universal percentage at which every application bottlenecks. NVIDIA says application behavior differs: some applications can use several times the available GPU memory, while others may become unstable as they approach the limit. NVIDIA’s separate report that certain professional RTX and Quadro workstation GPUs using its RTX Enterprise driver send Windows Event Log reports above 75% of available capacity is a product-specific notification rule, not a general cutoff for diagnosing a bottleneck. NVIDIA’s application-behavior guidance.
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What to do when evidence points to a memory limit
- Reduce the workload’s memory demand, such as by lowering memory-intensive application settings or using smaller assets where the application allows it.
- Repeat the same task and compare both the memory reading and the original symptom; a changed graph without a changed symptom may not solve the real issue.
- If the workload still exceeds the useful local-memory budget, evaluate hardware against that application’s actual needs. A general usage percentage alone cannot establish which GPU or capacity is appropriate.
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