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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Check the application’s own documentation and device settings first. It can use two Intel Arc GPUs only if its software supports multiple devices for the specific workload and exposes or implements a way to use them. Seeing two adapters in Windows or in a compute runtime does not prove the application will distribute work across both.
What “using both GPUs” means
Multi-GPU support depends on the workload and software stack. A game or renderer may need explicit multi-adapter support; a compute or media application may enumerate devices through a particular API and schedule work on more than one. A general statement that an app “supports multiple GPUs” is not enough unless it applies to your application version, operating system, backend, and the two Arc cards you have.
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Intel’s support article states, “Intel Arc® does not support GPU-to-GPU connection.” The article was last reviewed March 17, 2023. This refers to connecting Arc GPUs to work together as a general GPU-to-GPU arrangement; it does not establish that every compute or media application is incapable of selecting more than one device. Intel’s Arc multi-GPU support article
Deep Link is a different configuration
Intel describes Deep Link as combining a discrete Arc GPU with Intel Iris Xe integrated graphics in systems with 12th-generation Intel processors or newer. That is not a general bridge between two discrete Arc cards, nor does it mean an application will automatically use both devices. Intel’s description of Arc multi-GPU support
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How to check an application
- Identify the workload and devices. Note whether you want both GPUs to help with gaming, rendering, video processing, or compute. Record the exact Arc models, operating system, application version, and driver version.
- Check the application’s official documentation and release notes. Search for explicit multi-GPU, multi-adapter, or multi-device support. Confirm that the feature applies to your workload, operating system, graphics or compute API, and two discrete GPUs—not only to integrated-plus-discrete graphics.
- Inspect the application’s device controls. Look for a GPU-selection menu, a multi-GPU option, or backend settings. If the app lists devices, confirm both Arc GPUs appear and enable the relevant feature. A list of two devices is evidence of visibility, not evidence that the app assigns work to both.
- If it uses oneAPI or SYCL, check runtime discovery. Intel documents
sycl-lsfor showing devices visible to the SYCL runtime; multiple GPUs can appear as multiple root devices. On Windows, root devices may be exposed under different SYCL platforms. Follow Intel’s oneAPI Level Zero backend guide for the applicable setup and discovery details. Runtime visibility means the runtime can see a device; it does not show that the application has implemented multi-device workload distribution. - Run a representative task and observe both adapters. Check per-adapter activity while the application performs the workload in question. Activity on both is useful corroboration, but by itself does not prove both contributed to the same task, that performance improved, or that the configuration is officially supported. Where available, check application logs or profiler data as well. Intel’s troubleshooting guidance for highly parallel applications discusses current OpenCL and Level Zero drivers and profiling tools for oneAPI GPU work.
- Ask the application vendor if the answer is still uncertain. Provide the app version, operating system, driver version, both GPU models, API or backend, and the workload you tested. A driver setting cannot add a multi-GPU code path the application does not implement.
How to interpret what you find
| Observation | What it establishes | What it does not establish |
|---|---|---|
| Two Arc adapters appear in the operating system | Both are visible to the operating system. | That a particular app supports or uses both. |
sycl-ls or another runtime lists two devices |
The relevant runtime can discover multiple devices; Intel documents SYCL root-device enumeration. | That an application using that runtime distributes work across them. Intel’s 2026.0 device-discovery guide describes runtime discovery, not application-level support. |
| The app offers a multi-device control and lists both GPUs | The app exposes a relevant selection or configuration path. | That the chosen workload uses both correctly or benefits from doing so; verify with a representative task and, where possible, logs or profiling. |
| Both adapters show activity during a task | Both show activity during that observation. | That both contributed to the same task, that the activity was useful, or that the setup is supported. Corroborate with app documentation, logs, or profiler data. |
Intel’s Level Zero overview describes a programming interface for applications and runtimes targeting accelerator devices. Its existence does not mean every application uses Level Zero or supports multiple GPUs.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to compare when an app offers more than one mode
Compare the modes against the actual workload rather than assuming that more visible devices mean more performance.
Quick Recap
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- Dedicated Support: Please contact us directly through Amazon for any product questions or assistance you may require.
- Professional Intel Arc Pro B70 GPU: Built on the Intel Xe2-HPG architecture, it features 32 Xe cores and 256 XMX engines, designed to accelerate AI, rendering, and complex visualization workloads.
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- Workload type: graphics or rendering, compute, or media processing.
- API or backend used by the application.
- Whether both Arc devices are enumerated and selectable.
- Whether the app has an explicit multi-device control or documents automatic scheduling.
- Which GPU pairings, operating systems, and drivers the app supports.
- Whether a representative task shows both devices contributing, as confirmed by more than device visibility alone.
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