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On Windows, start with Task Manager → Performance and select the GPU your workload is using. NVIDIA users can also run nvidia-smi for device-level framebuffer memory readings; Intel integrated-graphics users should interpret memory figures as system-memory use, not a separate pool of physical VRAM. A high reading alone does not prove a bottleneck: watch memory while reproducing the workload and look for repeatable pressure alongside errors, instability, or performance changes.
Check GPU memory on Windows
Windows offers a built-in view, while vendor tools can add metrics or clarify what a reading represents. Menu names and available graphs can vary by Windows version, GPU, and driver.
Task Manager
- Press
Ctrl+Shift+Escto open Task Manager. - Select Performance, then select the relevant GPU.
- Inspect its memory graphs while the application or game is running. If the system has more than one adapter, confirm the workload is using the GPU you selected.
AMD documents GPU monitoring in Task Manager for Windows 10 Fall Creators Update and later, though the exact interface can differ across releases. See AMD’s Task Manager GPU monitoring guidance.
NVIDIA: nvidia-smi
Open a terminal or Command Prompt and run nvidia-smi. Where supported, the output reports device-level framebuffer memory, including total, reserved, used, and free amounts. NVIDIA documents the command and its supported metrics in the nvidia-smi reference.
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On Windows with the WDDM driver model, do not depend on nvidia-smi for per-process GPU-memory values: NVIDIA says Windows’ kernel-mode driver manages that memory and the per-process field is unavailable. The device-level figures may still be useful. On Linux, supported driver and GPU combinations can report framebuffer and utilization metrics; an unsupported metric may appear as a dash or be omitted.
Intel integrated graphics: DxDiag
Intel documents this route to view the reported dedicated-memory value: press Win+R, enter dxdiag, open Display Devices, and inspect Dedicated Memory. The figure needs context: Intel integrated graphics use system memory rather than a separate graphics-memory bank. Intel’s instructions are in its DxDiag graphics-memory guidance.
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AMD Software: Adrenalin Edition
AMD Software: Adrenalin Edition can display performance metrics such as GPU and memory usage through its PC-vitals and performance views. Availability and layout depend on the installed software and hardware; consult AMD’s performance-metrics guidance for the documented workflow.
Linux and virtualized NVIDIA systems
On a supported NVIDIA Linux system, nvidia-smi can report device memory and utilization metrics where the GPU and driver support them. A missing metric does not necessarily indicate zero use: NVIDIA’s documentation notes that unsupported values may be shown as a dash or left out.
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In an NVIDIA vGPU setup, the scope of a reading depends on where nvidia-smi runs. A guest VM’s view should not be assumed to describe the entire physical GPU; see the NVIDIA vGPU documentation for supported monitoring contexts. For AMD Linux systems, a single graphical monitoring path is not established across distributions, driver stacks, and GPU generations, so check guidance for the specific setup rather than assuming one tool is universal.
Know which memory a counter represents
Before comparing numbers, identify whether the tool shows device-wide framebuffer memory, memory attributed to a process, a local-memory segment, or system memory shared with graphics. Those values describe different pools and accounting scopes.
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| Monitor or platform | What the reading can show | Important limitation |
|---|---|---|
| Windows Task Manager | GPU memory graphs for the selected adapter | Confirm the workload is using that adapter; interface and detail vary by Windows release. |
NVIDIA nvidia-smi |
Device-level framebuffer totals and use; supported utilization metrics | Per-process GPU memory is unavailable in Windows WDDM mode. Accounting and supported fields vary by platform. |
| Intel integrated graphics | Dedicated-memory figure reported by DxDiag, plus Windows shared-system-memory context | Integrated graphics use system memory, not a separate physical graphics-memory bank. |
| AMD Software: Adrenalin Edition | GPU and memory usage performance metrics | Availability and layout depend on hardware and installation. |
Dedicated and shared memory on Intel integrated graphics
For Intel integrated graphics, Windows’ Shared System Memory figure is a limit the operating system may allow graphics to use, not an amount permanently reserved from system RAM. Intel also says its driver may report 128 MB of fictitious dedicated video memory for compatibility with applications that do not understand unified memory architecture. That compatibility figure does not establish that the GPU has a separate 128 MB VRAM bank. See Intel’s graphics-memory FAQ, last reviewed January 13, 2026.
A related, narrower feature applies to Ryzen AI 300 series and later: AMD describes Variable Graphics Memory as a BIOS-level reallocation of system RAM to integrated graphics. RAM converted to this dedicated allocation is no longer available to the CPU and system. It is platform-specific, not a generic method for adding physical VRAM to any GPU. Details are in AMD’s Variable Graphics Memory documentation.
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Framebuffer accounting on NVIDIA
NVIDIA uses “framebuffer” for a GPU’s on-board memory. The reported total can be affected by ECC and internal reservations; on GPUs exposed as OS-managed NUMA nodes, accuracy depends on operating-system accounting. Allocated pages may also remain after a process exits, and system memory pressure can affect reporting. As NVIDIA’s nvidia-smi reference explains, the displayed number is an accounting report, not an infallible view of every allocation’s owner.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Determine whether memory is the bottleneck
- Record the setup. Note the GPU, operating system, workload, driver mode where relevant, and the specific memory pool or counter shown.
- Measure during the workload. Reproduce the scene, project, or task that slows down and watch memory as it runs; an idle reading or a value sampled after the application exits may not describe the pressure during work.
- Look for repeatable symptoms alongside pressure. A reading that stays near the available local or framebuffer budget is a reason to investigate when it coincides with workload-specific errors, instability, or performance changes.
- Check other causes before concluding. Compare memory readings with GPU activity and other system indicators. A slowdown alone, or a single high percentage, does not isolate VRAM as the cause.
- Adjust the workload if evidence points to memory. Reduce memory-intensive settings or data demands and see whether the problem changes. Consider hardware with more suitable local memory only after measuring the needs of the specific application.
There is no universal percentage at which every application runs out of memory. NVIDIA notes that behavior differs: some applications can use several times the available GPU memory, while others may become unstable as they approach the limit. Its support guidance on GPU-memory usage, updated August 10, 2022, describes a separate, product-specific notification: certain professional RTX and Quadro workstation GPUs can send Windows Event Log reports above 75% of available capacity, once per process. That notification is not a general bottleneck threshold.
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