What Is Local AI? How to Run AI Offline on Your Windows PC
Local AI on PC lets you run compatible artificial intelligence models directly on your Windows computer instead of relying entirely on cloud-based services. You can use local AI for writing, summarizing documents, answering questions, and assisting with coding, depending on your chosen model and hardware. In this guide, you’ll learn how local AI works, how to run AI offline using tools such as Ollama and LM Studio, and what your PC needs to get started.
Microsoft is also expanding its approach to on-device AI. Its October 7, 2026, announcement describes Windows as a platform where AI can run locally when appropriate and use cloud computing when additional capabilities are needed.
But what is local AI processing, how does it work on a Windows PC, and can your existing computer run an AI model offline? Here is what you need to know.
What Is Local AI Processing?
Local AI processing is the process of running an artificial intelligence model directly on your computer instead of relying entirely on a remote server. The model uses your PC’s processor, memory, and, where supported, graphics hardware to generate responses.
For example, a cloud-based AI assistant typically sends your request to a remote service for processing. A properly configured local AI application can process the same type of request on your own device.
Local AI can support tasks such as:
- Writing, rewriting, and summarizing text.
- Answering questions about supported documents.
- Generating and explaining code.
- Organizing information and extracting key points.
- Running a personal AI assistant without a continuous internet connection.
However, local models vary in capability. A small model that runs comfortably on a laptop may not perform as well as a larger cloud model on complex reasoning tasks.
How Does Local AI Work on a PC?
A local AI model contains learned parameters that help it generate responses from your prompts. When you ask a question, the application processes your input and uses the model to generate an answer. This process is called inference.
Running local AI on PC gives you more control over your data and can let you use supported AI models without a continuous internet connection. However, performance depends on the model size, available RAM, processor, and GPU. Some models require an initial download, and certain features may still need internet access.
Three hardware components can play important roles.
1. CPU: The Main Processor
The central processing unit (CPU) can run compatible AI models without requiring a dedicated graphics card. This makes local AI possible on many existing computers, although generation speed depends on the processor, model size, and available memory.
2. GPU: Accelerating AI Workloads
A graphics processing unit (GPU) can accelerate AI inference when the software and model support it. Its available video memory, known as VRAM, can also limit which models run efficiently.
3. NPU: Hardware Designed for AI
A neural processing unit (NPU) is a specialized processor designed to accelerate supported AI workloads efficiently. Microsoft’s Copilot+ PC category requires an NPU rated at 40 or more trillion operations per second (TOPS).
An NPU is not mandatory for every local AI application. Compatible models can also run using a CPU or GPU.
How Microsoft Is Bringing AI to Windows PCs
Microsoft is developing Windows around a concept called hybrid intelligence: combining on-device AI with cloud-based AI rather than relying exclusively on either approach.
In its October 7, 2026, Windows hybrid intelligence announcement, Microsoft described a future in which AI agents can run locally when suitable, access cloud services when needed, and operate within Windows security and management controls.
The announcement is important, but readers should distinguish Microsoft’s direction from features that are already generally available.
What Is Microsoft Phi Silica?
Phi Silica is Microsoft’s small language model designed for on-device AI processing on Windows. It supports tasks such as text generation, summarization, and rewriting through compatible Windows applications.
Microsoft has also documented Phi Silica support on certain non-Copilot+ Windows 11 PCs using a supported GPU. Availability depends on the hardware, software version, and applicable API access.
Can You Run Local AI Without a Copilot+ PC?
Yes. Microsoft’s local language model documentation describes more than 20 open-source language models available through its development tools, with support for Windows 10 and later depending on the model and runtime.
You can also use independent applications such as Ollama and LM Studio. These options mean you do not necessarily need to purchase a new AI PC just to experiment with local language models.
How to Run AI Offline on Windows
If you want to try an AI model on your own computer, you can start with an application designed to manage local models.
Option 1: Use Ollama
Ollama lets you download and run supported language models on your computer. It is particularly useful for people interested in coding assistants, command-line tools, and local AI applications.
The basic process is straightforward:
- Visit the official Ollama website and install the Windows application.
- Choose a model compatible with your computer’s hardware and memory.
- Download the model while you have an internet connection.
- Run the model and test it with a simple prompt.
- Disconnect from the internet and verify that your chosen local workflow still works.
Some Ollama workflows use cloud-hosted models, so check that you have selected a model that runs locally.
Option 2: Use LM Studio
LM Studio provides a graphical interface for discovering, downloading, and chatting with compatible local models.
After downloading a model and completing the necessary setup, you can use supported chat and document features offline. Its offline documentation explains which functions continue working without an internet connection.
For beginners who prefer a visual interface over a terminal, LM Studio can be a convenient starting point.
Option 3: Use Microsoft Foundry Local
Developers can explore Microsoft Foundry Local to run supported models locally and integrate them into applications.
Microsoft’s documented quick-start requires Windows 11 version 24H2 or later, .NET 9 or later, and sufficient memory and storage. It also requires internet access to download the initial packages, models, and runtime components.
Once configured, compatible local inference can work without a continuous internet connection. This developer-focused option is different from simply opening Microsoft’s cloud-based Copilot service.
What PC Specifications Do You Need for Local AI?
There is no single hardware specification that works for every AI model. Requirements depend on model size, quantization, context length, and whether inference runs on the CPU or GPU.
| PC component | What to consider |
|---|---|
| RAM | More memory gives the model and other applications more room to operate. |
| CPU | A modern, compatible CPU can run smaller models, although performance varies. |
| GPU and VRAM | Useful for acceleration; larger models may need substantially more VRAM. |
| NPU | Helpful for supported, optimized AI workloads but not essential for every local model. |
| Storage | Leave enough free space for model downloads, which can occupy several gigabytes or more. |
As a practical starting point, a PC with 8 GB of RAM may be able to experiment with some small, quantized models, while 16 GB or more generally provides greater flexibility. Neither figure guarantees compatibility or good performance. Check the requirements of the specific model before downloading it.
If you are upgrading a computer, consider your overall system performance and storage needs as well. Our guide to SSD prices in 2026 can help you explore the storage side of a PC upgrade.
Local AI vs Cloud AI: Which Is Better?
Neither approach is universally better. The right choice depends on your task, hardware, privacy requirements, and internet access.
| Feature | Local AI | Cloud AI |
|---|---|---|
| Internet connection | Not required for supported offline workflows | Usually required |
| Data processing | Can remain on your computer | Processed by a remote service |
| Hardware requirements | Uses your PC’s available resources | Most model computation happens remotely |
| Model capabilities | Depend on the downloaded model | May provide access to larger models |
| Cost | No per-request cloud API fee for local inference; hardware and electricity still cost money | May require a subscription or usage-based payment |
| Updates and current information | May have outdated knowledge without external tools | Can access current information when supported |
Local processing can improve privacy, but it does not automatically guarantee it. An application may still transmit data through cloud features, plugins, telemetry, or external services. Check its privacy documentation and network behavior if sensitive information is involved.
Is Local AI Worth Using?
Local AI is worth exploring if you want offline access, more control over your models, or a way to experiment with AI without relying on a paid cloud API for every request.
It can be useful for drafting text, explaining code, summarizing documents, and learning how language models work. However, it is not a perfect replacement for every online AI service. Model quality, speed, and hardware limitations remain important considerations.
Before using any AI model for important decisions, verify its output against reliable sources. Local models can still generate incorrect or misleading information.
Frequently Asked Questions
Can I run AI on my PC without the internet?
Yes. Download a compatible model and the required software first. Once configured, supported local AI applications can generate responses offline. Features that depend on online services will still require connectivity.
Do I need a Copilot+ PC to use local AI?
No. Tools such as Ollama and LM Studio can run compatible models on ordinary Windows PCs. Performance and model compatibility depend on your hardware.
Can local AI help with programming?
Yes. Compatible coding models can explain code, suggest changes, and help with programming tasks. Their usefulness depends on model capability, context length, and your computer’s available memory.
Is local AI completely free?
Not necessarily. Many local models and applications are available without a per-request API fee, but you still need a computer, storage, electricity, and sometimes paid software or services.
Is local AI more private than cloud AI?
It can be. When a model and its processing remain entirely on your device, prompts do not need to be sent to a cloud model. However, the application and any connected services must also be considered.
Final Verdict
Local AI makes it possible to run compatible artificial intelligence models directly on your Windows PC, including in supported offline workflows. Microsoft’s Windows AI tools, Ollama, and LM Studio provide different ways to explore this technology, depending on your needs and hardware.
Microsoft’s hybrid-intelligence strategy signals a growing role for AI that combines local processing with cloud capabilities. For everyday users, the best starting point is to choose a small, compatible model, test it on existing hardware, and verify that it works offline before depending on it.
You do not necessarily need a new AI PC to begin. Start with the computer you already own, understand its limitations, and upgrade only when your preferred models require more resources.
