ChatGPT and Gemini rely on large language models that are now embedded in daily work, from writing code to searching the web. These tools will remain central to the industry regardless of where they go next.
While you likely use these models through platforms like Perplexity or Claude, the same software can run on your own machine. This setup keeps data offline and away from cloud servers. You also avoid monthly fees and usage limits. Several models from major companies are available for free download. They may not match the speed or sophistication of paid services, but they handle everyday tasks well. You can switch between different versions as you see fit.
Running the software locally requires more maintenance than using an app. You must manage updates yourself. In return, you gain a private system that does not send your prompts to a third party. Getting started is not difficult.
Hardware Requirements
Windows, macOS, and Linux all support local models. Macs are generally preferred by enthusiasts. The ecosystem is unified because a single company manufactures them. Apple Silicon chips combine the CPU, GPU, and RAM in a way that suits AI processing.
RAM capacity matters. Eight gigabytes is the bare minimum, but it limits the size and speed of the models you can run. Sixteen gigabytes is better. Thirty-two gigabytes or more is needed for the largest and fastest versions. A dedicated graphics card with at least eight gigabytes of VRAM helps significantly. This memory type is optimised for the specific tasks AI models perform.
On Windows, an Nvidia GPU provides a major boost. Graphics chips handle AI processes better than standard processors. This link explains why Nvidia and the current AI boom are so closely connected. These cards include their own memory, giving models extra space to operate.
There is no strict minimum specification. More RAM and a discrete graphics card will certainly improve performance. You also need software to act as an interface, plus the model file itself. Many choices exist for both.
LM Studio is widely considered the best application for Windows and macOS. It is free to use. Other trusted options include vLLM, Llama.cpp, Ollama, and GPT4All. These tools work across multiple operating systems but require more technical knowledge.
Once you have chosen your software, you must select a model. The programs mentioned will suggest options. You can also browse online repositories. Hugging Face is the most well-known site, hosting more than 3 million models.
Setting Up LM Studio
Many configurations are possible, but this guide walks through installing LM Studio on Windows. Download the installer from the website and launch the application. Click Create Project to begin and name your first project.
A blank chat window appears. Click Choose a model in the prompt box, then select Get local models to open the main picker. LM Studio lists available versions with their size, popularity, and details. Staff picks offer good starting recommendations. Smaller models download faster and use less system space, though they are less capable.
The chat interface works like a standard bot. You can switch between installed models in the bottom prompt box. A plus icon on the left allows you to submit images and files if the current model supports them.
The left navigation pane lets you switch between projects. The Settings link in the lower left opens a preferences screen. You can customise how deleted chats are handled and adjust onscreen elements.
Click Library in Settings to manage existing models. Use the Explore menu to find new ones. For image and document support, search for multimodal models. These tools build on standard language capabilities but are often referred to as LLMs.
The right-hand sidebar can be toggled on or off via the top-right button. It offers options for managing files across projects and granting the program access to your computer’s file system.
