A local AI PC can chat, summarize and rewrite text, work with documents you have loaded, recognize text in images, describe or create images, transcribe speech, and provide some coding help without internet access—provided the required app, model, and files are already on the computer. Offline capability depends on the specific software and hardware; an “AI PC” label alone does not guarantee that every feature will work offline.
What you can do offline with local AI
When a model is installed or cached, its inference can happen on your PC rather than through a cloud service. The available tasks depend on the runtime, model, and device.
Ask questions and work with text
Local language models can answer prompts, draft short content, summarize material, and rewrite text. Microsoft describes Phi Silica as a small language model optimized to run locally on the NPU in supported Copilot+ PCs. Other runtimes provide access to different local models. The model’s quality and speed depend on the hardware and model selected.
Ask questions about your own documents
A local model can be paired with documents or other data that you have added to a local search or retrieval workflow. Dell’s Airgap AI example uses PDFs, policies, and sales decks as a dataset for answering questions. That is a workflow example, not a guarantee that every app can read every file type or that every answer will be correct. Check answers against the source documents, especially for important decisions.
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Recognize text and describe images
Windows AI options include optical character recognition (OCR) and image-description capabilities. Microsoft’s Windows AI solution comparison lists these among available tasks, but device and API support varies. You may be able to extract text from an image or get a description without sending it to an online service when using a supported local feature.
Create or edit images
Some Windows AI components support local image generation and image processing, including workflows such as extracting or removing an object. These capabilities are tied to supported hardware and software; they are not a standard feature of every PC or third-party image app.
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Transcribe speech
Foundry Local’s model catalog includes voice-to-text options. Supported languages, accuracy, and processing speed vary by model, so confirm that the model covers the language and recording conditions you need before relying on it offline.
Get some coding help
Visual Studio Code documents chat with local models without an internet connection. Its service-dependent features—including semantic search, inline suggestions, and embeddings—are unavailable offline according to the Visual Studio Code language-model documentation. Local chat should not be mistaken for the full set of capabilities in a cloud-connected coding assistant.
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What “offline” does—and does not—mean
Offline use means a compatible model can process your prompt on the PC without depending on a cloud inference service. Microsoft says that Foundry Local performs inference on-device after a model has been downloaded and cached. Its privacy FAQ says that the runtime’s inputs and outputs stay on-device; it identifies the initial model download and optional catalog metadata refreshes as network traffic. These statements apply to Foundry Local, not automatically to every AI app that advertises local features.
Setup, sign-in, model downloads, updates, and adjacent app features can still require a connection. A local model also cannot fetch current web information while disconnected. It can use local information you prepared in advance, but its answers will not include live updates unless you reconnect or provide an offline data source.
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Local processing can reduce the need to send prompts and outputs to a cloud service, but verify the behavior of the particular app and runtime you use. “Runs locally” does not establish that every part of an application is offline or that its outputs are accurate.
Does your PC need to be a Copilot+ PC?
No—not for all local AI. Microsoft says most built-in Windows AI APIs require Copilot+ hardware, while Foundry Local and Windows ML do not require Copilot+ status. The options differ in what they provide and how models are supplied.
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| Option | What it provides | Hardware and model considerations | How models are supplied |
|---|---|---|---|
| Windows AI APIs | Ready-to-use Windows AI capabilities, such as language, OCR, and image-related features | Most require Copilot+ hardware; feature availability varies by device | Models are acquired at runtime, according to Microsoft’s Windows AI solution comparison |
| Foundry Local | A catalog and runtime for local language-model and speech scenarios | Can use a supported GPU, NPU, or CPU fallback; not every model is available on every hardware configuration | Download and cache a compatible model before disconnecting |
| Windows ML | A framework for apps that bring ONNX models and manage execution providers | Does not require Copilot+ status; compatibility depends on the model and execution path | Model distribution is handled by the app |
Microsoft defines a Copilot+ PC as having an NPU rated at 40 or more TOPS, at least 16 GB of RAM, and a supported SoC. Those are requirements for that product category, not universal minimum requirements for every local model or runtime. A non-Copilot+ PC may still run local AI through a supported CPU, GPU, or NPU path, although available models and performance can differ. Microsoft’s comparison of Windows AI solutions and Windows AI FAQ describe these distinctions.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Prepare a PC before you go offline
- Choose the task. Decide whether you need chat, document questions, transcription, image processing, or coding help. Each may require a different model or app.
- Check the runtime and device. Confirm that the app supports local operation and that its model runs on your PC’s CPU, GPU, or NPU. Do not assume that “AI PC” guarantees compatibility.
- Download the app and model while connected. Foundry Local requires an internet connection for the initial model download. The model must be cached on the device before it can perform offline inference.
- Prepare your files and data. Add or index the documents, images, and other material you will need. A model cannot answer questions about files it has not been given or retrieve live web information while offline.
- Test the actual offline workflow. Disconnect from the internet and try the exact task, files, and language you plan to use. Check that the app opens, the model loads, and any required local indexes are available.
There is no reliable universal estimate for model speed or quality across PCs. Results depend on the specific machine, model, model configuration, and workload; the available documentation does not establish a device-independent benchmark or a model-size recommendation that applies to every PC.
Quick Recap
When local AI is useful—and when it is not
- Useful: drafting or summarizing material when you are disconnected; searching a prepared set of local documents; transcribing supported speech; or processing content with a local feature when you do not want to rely on a cloud inference service.
- Less suitable: questions that need current web facts, work that depends on an online account or cloud service, or a workflow that has not been tested on your hardware and files.
- Always verify: model-generated facts and document answers. Offline access changes where processing occurs, not whether an answer is correct.
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