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A physical GPU name does not establish the resources available to a vGPU instance. Verify the selected profile and the actual application workload together.
VK Cloud offers Cloud GPU resources for virtual machines, including documented vGPU options. First establish whether the application needs a full accelerator or an available virtual profile. A physical card name without the allocated VRAM and resource format does not completely describe what the application receives.
Confirm the product and requirement
The official Cloud GPU page confirms the service and inquiry process. It is not current inventory for every advertised variant. Prepare minimum VRAM, system RAM, simultaneous tasks, operating system and whether a custom image is required.
Check current access and ordering conditions for the actual organisation and location. A Russian-language product page can be a valid technical source without implying that the product or a payment route is available to every international reader.
Distinguish a full GPU and vGPU
The official VK Cloud documentation repository describes virtual profiles and their memory allocation. vGPU has separate driver and licensing requirements. Do not infer a profile’s usable memory from the physical device’s total capacity.
| Criterion | Full GPU | vGPU |
|---|---|---|
| Resource arrangement | Physical accelerator allocation | Supported virtual profile |
| Memory check | Selected GPU configuration | Selected profile allocation |
| OS preparation | Compatible GPU driver | vGPU driver and licensing setup |
| Custom image | Compatibility work | Additional licensing-token checks |
This is a resource distinction, not a claim that one option wins for every AI task. The actual application and configuration determine suitability.
Prepare the image correctly
The documentation distinguishes a prepared provider image from a custom system in licensing setup. For a custom image, establish the required steps and access to licensing before diagnosing model behaviour. A preparation issue can otherwise resemble an application or device problem.
Record image, driver and configuration in the pilot report. Put manual changes into the recipe so another VM does not depend on one unrecorded session. Test accelerator visibility and the expected available memory before the main workload.
Test the intended concurrency
Start with a small research input, verify the result and export it. If memory is insufficient, base the next choice on measured demand rather than assuming access to all physical-card VRAM.
Include the intended number of simultaneous processes. One small job can work while several require another profile. Record process count, input size and observed consumption, then decide how files and resources will be retained after the test. Closing a notebook does not establish that the associated services are no longer billable.
Turn the check into a practical next step
A physical GPU name does not establish the resources available to a vGPU instance. Verify the selected profile and the actual application workload together.
For the documented details, consult the primary documentation; configuration reference. Continue with cloud gpu ephemeral vs persistent checklist and cloud gpu account team key rotation.