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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →On-device AI in Windows means that a model performs its inference on your own PC instead of sending the input to a cloud service. The work may use a neural processing unit (NPU), CPU, or GPU. That can improve data control and allow some features to continue without an internet connection, but “on-device” does not mean that every part of a feature is permanently offline. A model may need to be downloaded first, an app may refresh online data, or a follow-up action may send selected text to a provider.
Windows has several local-AI routes rather than one universal Windows AI switch: built-in Copilot+ PC experiences, applications using local language models, and developer frameworks such as Windows ML. What works offline depends on the exact feature, Windows build, language, hardware, driver, and whether its required model and setup are already present.
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What “on-device AI” means in Windows
In a cloud AI workflow, your PC uploads a prompt, image, audio stream, or other data to a remote service for inference. With on-device AI, the model calculations happen on the computer. Windows can schedule that work on an NPU designed for sustained AI operations, a CPU, or a GPU, depending on the feature and the model.
Microsoft describes Windows AI as a combination of on-device models, NPU acceleration, and cloud APIs. Its Windows AI overview therefore does not promise that every Windows feature is local. “Local inference” answers where a particular calculation occurs; “offline availability” asks whether the whole user action can complete without a network connection. Those are different questions.
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- A local feature can still require an internet connection for its first model download, account setup, catalog refresh, or online data.
- An application can analyze content locally and then offer a separate action that sends the selected content to an online provider.
- A feature can be available only on a particular Windows release, language, NPU, driver, or PC configuration.
Microsoft’s developer guidance summarizes the hardware goal this way: “The NPU enables on-device AI experiences including Windows Copilot+ PC features.”
The three Windows paths for local AI
Built-in Windows and Copilot+ PC experiences
Features integrated into Windows are the most visible form of on-device AI. Examples include Recall, local text actions in Click to Do, and Windows Studio Effects. Many of these experiences target Copilot+ PCs with an NPU rated at more than 40 trillion operations per second (TOPS). Microsoft’s Copilot+ PCs developer guide identifies Snapdragon, AMD, and Intel device families, but eligibility is feature-specific. A computer marketed as an “AI PC” is not automatically eligible for every Copilot+ function.
Apps that run downloaded models
An application can package or download an open-source language, vision, or speech model and run it on your hardware. Microsoft’s Foundry Local is one route for this style of deployment. The model must be downloaded and cached while you are online; after that, compatible models can perform inference while the PC is disconnected.
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Developer frameworks
Microsoft’s Windows AI platform also includes Windows AI APIs for built-in Copilot+ functionality and Windows ML for deploying ONNX models. Windows ML can select an execution provider for available hardware, so a developer can target local inference without assuming that every PC has the same accelerator. The application, model, and installation determine whether the finished program works offline; Windows ML itself is not a consumer feature with one universal offline guarantee.
What can work without the internet?
The table separates local processing from the preparation and network conditions that surround it. “Offline after setup” means the documented local part can continue after required downloads and configuration have been completed; it does not promise that every related feature in the same app is disconnected.
| Feature or route | What runs locally | Offline conditions and limits | Hardware or software conditions |
|---|---|---|---|
| Recall | Snapshots are analyzed and stored on the PC. | Microsoft says no internet or cloud connection is required or used to save and analyze snapshots. Initial configuration and supported hardware are required. | Copilot+ PC requirements listed by Microsoft include a 40 TOPS NPU, 16 GB RAM, 256 GB storage, and at least 50 GB of free storage to enable Recall. |
| Click to Do text actions | Phi Silica performs certain text actions locally on Copilot+ PCs. | Summarize, Create a bulleted list, and Rewrite are listed for English. Other Click to Do choices can send selected content to an online provider, so the entire workflow is not necessarily offline. | Requires a supported Copilot+ PC feature configuration; language and action availability vary. |
| Windows Studio Effects | Supported camera and microphone effects are applied on the device. | Effects can work without a cloud inference request once the required driver and hardware are present. Video-call or app services may still need the internet for the call itself. | Windows 11 version 22H2 or newer, a supported NPU, and an enabled manufacturer-installed driver. |
| Foundry Local | A downloaded model performs inference on the PC. | The first model download requires internet. Cached model files can then be used while disconnected; catalog metadata may refresh at startup but cached information can be used offline. | A dedicated GPU, NPU, or Copilot+ PC is not mandatory when the chosen model has a compatible CPU variant. |
| Windows ML applications | The app runs an ONNX model through a suitable local execution provider. | Offline operation depends on the app’s model packaging, installation, and any network-dependent features around it. | Hardware support and performance vary by model and execution provider. |
Recall: Microsoft’s clearest local example
Recall periodically creates snapshots of activity so you can search and revisit what was on screen. Microsoft says those snapshots are analyzed and stored on the PC, and that an internet or cloud connection is not required or used to save and analyze them. This is a statement about Recall’s documented processing path, not a promise that every Windows search or connected application is offline.
Microsoft’s Recall application card lists these requirements for the supported configuration:
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- A Copilot+ PC with a 40 TOPS NPU.
- At least 16 GB of RAM.
- At least 256 GB of storage.
- At least 50 GB of free storage to enable Recall.
You must complete Recall’s initial configuration before snapshots can be collected. Availability, supported devices, and Windows build requirements can change, so check Microsoft’s current Recall management documentation for the particular device and release. These figures describe Recall’s documented requirements; they are not minimum requirements for all local AI on Windows.
Click to Do: local analysis does not make every action offline
Click to Do presents actions for content Windows detects on screen. On Copilot+ PCs, Microsoft says Phi Silica handles certain text actions locally. The English options documented by Microsoft include Summarize, Create a bulleted list, and Rewrite. The retrieved documentation describes a more limited subset for French and Spanish, so language support should be checked rather than assumed.
The important boundary is what happens after detection and local analysis. Some Click to Do choices send the selected content from the device to an online provider. If you need a strictly offline workflow, read the description of the individual action and avoid options that identify an online provider or require a connection. Treat “Phi Silica runs locally” as a statement about those particular text operations, not about every Click to Do command.
Feature behavior and language coverage can change with Windows updates. Microsoft’s Click to Do management page is the authoritative place to verify the current action list.
Windows Studio Effects: local camera and microphone processing
Studio Effects can process supported camera and microphone effects on a compatible Windows PC. Microsoft lists background blur, eye contact, auto framing, voice focus, portrait light, creative filters, and an eye-contact teleprompter effect among the supported effects. The effect is local processing, while the meeting or recording application may still need a network connection for its own service.
Microsoft’s Studio Effects overview specifies three practical prerequisites:
- Windows 11 version 22H2 or newer.
- A supported NPU.
- An enabled driver installed by the PC manufacturer.
To check availability, open Quick Settings and look for Studio Effects, or open Settings > Bluetooth & devices > Cameras. If the controls are missing, the cause may be an unsupported NPU, an outdated or disabled manufacturer driver, an unsupported camera, or a Windows version below 22H2. Installing a generic camera driver is not guaranteed to provide the required AI effects because Microsoft calls for the manufacturer-enabled driver.
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Foundry Local: offline models after the first download
Foundry Local is intended for applications and developers that want to run compatible open-source language models on Windows. The workflow has two distinct phases:
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- Run from the cache. Once the model files are present, inference can continue locally while the computer is disconnected. Foundry Local may try to refresh catalog metadata at startup, but Microsoft says cached information can be used offline.
A Copilot+ PC is not required for every Foundry Local scenario. Microsoft notes that a selected model may have a CPU-compatible variant, allowing local inference on a conventional Windows PC. Other models may benefit from or require a GPU or NPU. Compatibility, memory use, response speed, and output quality depend on the exact model and hardware; Microsoft’s documentation does not establish one universal performance figure.
Use Microsoft’s Foundry Local getting-started guide for the current installation and model-selection process. Do not delete the model cache if you expect the application to work offline.
Windows ML and custom local models
Windows ML is a developer framework for deploying ONNX models locally. It can select among available execution providers, which may include CPU, GPU, or an NPU-backed path when the device and driver support one. This makes it useful for custom vision, speech, classification, or language features embedded in a Windows application.
For an end user, offline behavior is determined by the finished application rather than by the framework name. An app may package its model and run completely offline, download the model on first launch, check a license online, or call a cloud API for an optional feature. Ask the developer whether the model is installed locally, whether updates are optional, and which actions make network requests. Microsoft’s Windows ML overview explains the deployment framework without promising a single consumer feature or hardware requirement.
Do you need a Copilot+ PC for Windows AI?
You need a supported Copilot+ PC and qualifying NPU for many of the newest built-in experiences, but not for all local AI. Microsoft describes 40+ TOPS as a requirement for many new Windows AI features. That threshold is a hardware eligibility measure, not a guaranteed speed, battery-life, or model-quality benchmark.
Foundry Local illustrates the distinction: a compatible CPU model can run without a dedicated GPU, NPU, or Copilot+ designation. Conversely, a PC can have an NPU and still lack a required Windows build, driver, language pack, storage space, or feature rollout. Before buying or upgrading, verify all of the following for the exact configuration:
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- The advertised NPU TOPS rating and whether Microsoft lists that device family as Copilot+ eligible.
- The Windows 11 edition and build required by the feature.
- Manufacturer drivers, firmware, and camera or microphone support.
- RAM, storage, and free-space requirements for the particular feature.
- Supported languages and regional availability.
- Whether the application supplies a downloadable local model or depends on a cloud service.
How to check whether a task is really offline
Use this checklist before handling sensitive material or relying on a feature during travel:
- Name the exact task. “Windows AI” is too broad; identify Recall, a Studio Effect, a Click to Do action, a local chatbot, or a custom app.
- Separate inference from setup. Confirm whether the model, catalog, language pack, or feature configuration has already been downloaded.
- Check hardware and software. Verify the NPU, Windows build, driver, RAM, storage, and language requirements listed for that feature.
- Inspect the network boundary. Look for wording about online providers, web results, account authentication, synchronization, or content upload.
- Test with the connection disabled. After preparation, disconnect Wi-Fi and Ethernet and repeat the specific action. A failure may indicate an online dependency even when another part of the feature is local.
- Restore connectivity for maintenance. Model updates, security fixes, catalog refreshes, and feature updates may require an internet connection later.
Privacy and practical limitations
Keeping inference on the PC can reduce the need to upload raw content for that calculation, but it is not a blanket privacy guarantee for every application. A third-party app can collect telemetry, synchronize files, or offer cloud actions around a local model. Review the app’s privacy controls and identify which buttons cross the network boundary.
Local processing also has trade-offs. Large models can consume RAM and storage; CPU-only variants may be slower than an accelerator-backed version; and an NPU-supported feature may still be unavailable because of a driver or Windows release. Microsoft’s retrieved pages do not provide a controlled comparison of speed, battery savings, latency, or answer quality across specific PCs. Those outcomes depend on the model, workload, thermal limits, and execution path.
Common failure cases and fixes
The feature is missing
Check the Windows version, feature rollout status, exact PC model, NPU capability, language, and manufacturer driver. “AI PC” branding alone is not sufficient evidence of eligibility.
Offline use stops after setup
Confirm that the model is fully downloaded and cached, then check whether the action itself calls an online provider. Foundry Local can use cached model data, while a catalog refresh or an optional cloud action may still fail without connectivity.
Studio Effects controls are unavailable
Open Settings > Bluetooth & devices > Cameras and verify the camera, Windows 11 22H2-or-newer status, supported NPU, and manufacturer-enabled driver. Contact the PC maker if the required driver is not offered.
Recall cannot be enabled
Compare the device with Microsoft’s Recall application-card requirements, especially 40 TOPS NPU capability, 16 GB RAM, 256 GB storage, and 50 GB of free space. If the machine fails any of those documented conditions, another local-model route may still work, but Recall will not be a general Windows AI substitute.
The bottom line
Windows on-device AI is a collection of local inference paths, not a single offline mode. Recall and selected Studio Effects are designed to process locally on supported Copilot+ hardware; selected Click to Do text actions use local Phi Silica but can hand content to online providers; Foundry Local works offline after its model is downloaded; and Windows ML lets developers ship their own local ONNX workflows. To know whether a task works without the internet, identify the exact feature, complete its required downloads, verify the hardware and Windows version, and check every follow-up action for a cloud dependency.
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