Large language models that power services like ChatGPT and Gemini can be run locally on a personal computer, avoiding cloud-based data sharing and subscription fees. Many users are already familiar with LLMs through hosted AI platforms, but local operation offers offline access and privacy, as nothing is sent to the cloud for review. While local models are generally less advanced or speedy than the ones inside paid apps, they remain capable for everyday tasks, and users can switch between multiple free options from companies such as Meta and Google.
Local LLMs work on Windows, macOS, and Linux, with macOS often preferred by hobbyists due to its unified hardware and Apple Silicon chips, which combine CPU, GPU, and RAM. The minimum RAM requirement is 8 GB, though 16 GB is better, and 32 GB or more is needed for the largest and fastest models. A dedicated GPU with more than 8 GB of VRAM, especially an Nvidia card on Windows, significantly improves performance because graphics chips are better suited for AI processing than standard processors.
The software layer, or outer interface, is separate from the model itself. LM Studio Bionic is widely considered the best free choice for Windows and macOS, with other trusted options including vLLM, Llama.cpp, Ollama, and GPT4All, though those are more technical. Models can be sourced from online repositories, with Hugging Face hosting more than 3 million downloads.
Setup for LM Studio Bionic on Windows begins with downloading the installer and launching the program. Users click Create Project, name it, and then select Choose a model in the prompt box, followed by Get local models, to open the model picker. Each model is listed with its size, popularity, and description, and staff picks highlight recommended options; smaller models download faster and take less space but are less capable.
The chat interface resembles standard AI chatbot apps, with a prompt box at the bottom to choose between installed models and a plus icon to submit images or files if the current model supports them. The left navigation pane allows switching between projects and includes a Settings link for customizing preferences such as how deleted chats are handled and which interface elements appear. The Library section in Settings manages existing models, while the Explore menu finds new ones, and users should look for multimodal models if they need image or document support.
A right-hand sidebar, toggled by a button at the top-right corner, provides options for managing files across projects and giving the program access to the computer鈥檚 file system. The entire setup runs privately and offline, though users must handle updates themselves. For US consumers concerned about data privacy or recurring costs, local LLMs offer a self-contained alternative, but they require more maintenance than simply opening a hosted app.
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