Run large language models on your own computer for offline access and more privacy. Find out what hardware you need, which apps to try, and how to get started-no subscription required.
Large language models now power tools like ChatGPT, Claude, Perplexity, and Gemini, handling everything from code suggestions to writing help. Most people use these models through cloud services, but you can increasingly run them directly on your own computer. This keeps your data private and lets you use AI offline, without monthly fees or sending information to outside servers.
You can download several LLMs for free, including some from Meta and Google. Local models may not be as fast or advanced as cloud versions, but they work well for everyday tasks and let you choose what fits your needs. Running a local LLM means you handle updates and pick your own models, but you get more privacy and control in return.
In 2026, Perplexity introduced Portable Computer-a fully local AI agent system where all orchestration and sub-agents run entirely on the user's device, with no cloud dependency.
System requirements
You can run local LLMs on Windows, macOS, or Linux. Many users prefer macOS for its unified hardware and Apple Silicon chips, which combine CPU, GPU, and RAM. No matter the platform, having enough RAM is important. 8 GB is the bare minimum, but it limits which models you can use and how fast they run. 16 GB is better, and 32 GB or more is best for the largest models. A dedicated GPU with at least 8 GB of VRAM helps a lot, especially on Windows with Nvidia cards.
There is no strict minimum, but more RAM and a discrete GPU will make things smoother. Once your hardware is ready, you need both an app to run the model and the model file itself. Popular free apps include LM Studio Bionic (for Windows and macOS), vLLM, Llama.cpp, Ollama, and GPT4All. These work across different operating systems and range from beginner-friendly to more technical.
Meta and Alibaba have become key providers of open-weight models for local deployment, with recent releases like Meta Muse Glimmer and Qwen specifically designed for local or partially local use.
Choosing and installing a model
After picking an AI app, choose an LLM. Most apps point you to compatible models, and sites like Hugging Face host millions of options. Smaller models download faster and use less storage, but may be less capable. Many apps, including LM Studio Bionic, highlight recommended models to help you get started.
Setting up LM Studio Bionic on Windows is simple. Install the app, create a new project, and name it. In the conversation window, select "Choose a model" and then "Get local models" to browse options. Each model lists its size, popularity, and key details. Once you download a model, you can chat with it in an interface similar to other AI chatbots. The app lets you switch between models, upload images or files (if supported), and manage projects from a navigation pane.
Customizing your local AI
LM Studio Bionic has several settings for customization, from chat deletion to interface tweaks. The "Library" section manages installed models, while "Explore" helps you find new ones. If you need image or document support, look for multimodal models, which add extra features. The right-hand sidebar gives you tools for managing files and letting the app access your computer's file system as needed.
Running a local LLM takes more setup and maintenance than using a cloud AI service, but you get full control over your data and how your AI works. With the right hardware and software, anyone can build a private, offline AI assistant that fits their needs.
