You can run an AI assistant on your computer by installing a model runner, downloading model weights that fit your hardware, and loading them before you chat. For a single-app graphical setup, LM Studio handles model discovery, loading, and chat. For a modular setup, Ollama runs the model and can be paired with a separate interface such as Open WebUI. What “local” means for privacy depends on which model and connected features you use.
Choose a setup path
There are two practical starting points: an all-in-one desktop app or a model runner with a separate chat interface. Neither is universally better; choose based on how much configuration you want and whether you need a browser-based interface.
| Route | What you install | Best fit | Important consideration |
|---|---|---|---|
| LM Studio | One desktop application for finding models, loading them, and chatting | People who prefer a graphical, integrated workflow | Check the current system requirements and the details and license of each model before downloading it. LM Studio’s getting-started guide |
| Ollama with Open WebUI | Ollama as the model runner, plus an optional separate interface | People who want a modular setup or a browser-based chat interface | Open WebUI can connect to local Ollama models and to hosted providers, so check the selected connection. Open WebUI documentation |
Before you install: check compatibility and space
Match the model to available memory
Model size affects whether it can load and how responsive it feels. LM Studio explains that loading a model allocates memory for its weights and other parameters; Ollama notes that larger models are slow without a strong GPU. Check the specific model’s memory requirements against available system memory and GPU memory, leaving capacity for the operating system and other applications. There is no single minimum specification that applies to every model and computer. Ollama summarizes the trade-off plainly: “Speed depends on the hardware.” Ollama download page · LM Studio getting-started guide
Plan for model storage
Ollama’s Windows documentation, accessed October 4, 2026, says its binary installation needs at least 4 GB; that does not include model files. Ollama says model files may require tens to hundreds of GB, depending on the models chosen. Its Windows and macOS documentation explain how to change the model storage location. If internal storage is tight, an external SSD is an option, but choose its capacity after checking the actual sizes of the models you plan to keep. Ollama Windows documentation · Ollama macOS documentation
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Verify your operating system’s current requirements
Requirements can change, so use the platform documentation linked here before installing. Ollama’s Windows guide lists Windows 10 version 22H2 or newer and documents driver conditions for NVIDIA and AMD acceleration. Its macOS guide lists macOS Sonoma 14 or newer; Apple M-series systems use CPU and GPU support, while x86 systems are CPU-only. Ollama Windows documentation · Ollama macOS documentation
Option 1: Set up LM Studio
- Install LM Studio using its current official instructions.
- Open Discover and download a model. LM Studio names Qwen, Mistral, Gemma, and gpt-oss as examples; availability and requirements can change, so check the current model details rather than treating any example as a universal recommendation.
- Use the model loader to select and load the downloaded model. Loading allocates memory for the model’s weights and other parameters.
- Open Chat and start a conversation. If loading fails or performance is poor, check the selected model’s requirements against available memory and try a model that better fits your computer.
LM Studio cautions that models vary in license and in how open they are. Review the license for the model you intend to use, especially if your use has legal or commercial requirements. LM Studio: Get started
Option 2: Run Ollama with Open WebUI
Install Ollama
Ollama’s official download page provides these commands. Because installation instructions can change, confirm the current command on that page before running it.
- macOS or Linux:
curl -fsSL https://ollama.com/install.sh | sh - Windows PowerShell:
irm https://ollama.com/install.ps1 | iex
On Windows, Ollama runs as a native background application and serves a local API at http://localhost:11434. That address is on your computer; it is the local service endpoint, not a chat interface by itself. Ollama download page · Ollama Windows documentation
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Add an interface if you want one
Open WebUI is a separate option for interacting with a model. Its official documentation lists Docker, pip, uv, and a desktop app as installation routes. Follow the current instructions for the route you choose, then configure the interface to connect to Ollama if you want to use a local Ollama model. Open WebUI can also connect to hosted providers, so installing it does not by itself ensure that requests stay on your computer. Open WebUI documentation
Open WebUI reports that, as checked September 28, 2026, its compressed Linux/amd64 Docker image downloads were 176 MB for :slim and 1.66 GB for :main. These are container image sizes, not model sizes or a guarantee of total installed storage. Open WebUI documentation
What “local” means for your data
When a selected model runs locally, the model computation takes place on your computer. That does not mean every feature in an assistant setup is local. Ollama distinguishes local models from its cloud models, which run on Ollama’s servers. Open WebUI can connect to Ollama as well as hosted providers including OpenAI and Anthropic. Web search, hosted APIs, cloud models, and other integrations may send prompts or related data beyond your computer.
- Check which model or provider the chat interface is using.
- Check whether search, file processing, or other connected features rely on remote services.
- Do not assume a setup offers complete privacy merely because a local runner is installed; verify the data path of the exact features you enable.
Ollama download page · Open WebUI documentation
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Troubleshoot common setup problems
The model will not load
Check that the model files have finished downloading, then compare that model’s memory needs with available system and GPU memory. Close other demanding applications or select a model with requirements that better match the computer. A runner’s installation space and the model’s storage and memory needs are separate constraints.
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Responses are too slow
Performance depends on the specific model and your CPU, GPU, memory, and configuration. Ollama warns that larger models are slow without a strong GPU. Try a smaller model if speed matters more than using a larger one; do not assume that performance reported for another computer will carry over to yours.
You are running out of disk space
Check the sizes of the downloaded models and remove models you no longer need. Ollama documents how to change model storage location on Windows and macOS, which can help when another drive has more room. Windows storage instructions · macOS storage instructions
The chat interface is not using the local model
Confirm that the interface is connected to your local Ollama service or that LM Studio has the intended model loaded. In Open WebUI, inspect the configured provider and selected model: the interface supports hosted providers as well as Ollama, and choosing a hosted connection changes where inference runs. Open WebUI documentation
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