Best way to run a local LLM (2026)
Running an AI model on your own machine means no subscription, no rate limits, and no data leaving your network. It's easier than it looks now — here's the shortest path from "curious" to "chatting with a private model."
The two decisions
- Which app runs the model?
- Does your hardware have enough memory? (For local AI, memory is king — VRAM on a GPU, or unified memory on Apple Silicon. It caps the model size you can run.)
The apps
| Tool | Best for | Notes |
|---|---|---|
| Ollama | The easiest start | One command to pull and run open models. Great CLI + API other apps can use. |
| LM Studio | Non-terminal folks | Polished desktop app to browse, download, and chat with models. |
| Open WebUI | A ChatGPT-style face | Self-hosted web UI that sits on top of Ollama — perfect on a homelab box. |
| Jan | Fully offline/private | Open-source, offline-first assistant; everything stays local. |
The hardware
- Mac (Apple Silicon): unified memory makes even a Mac mini a shockingly capable, quiet local-AI box for small and mid-size models.
- PC with an NVIDIA GPU: buy the most VRAM you can afford — a used 24GB card runs far bigger models than an 8GB one.
- Tiny always-on: a small board can run small models for automations at the edge.
The 15-minute starting path
- Install Ollama.
- Pull a small, well-regarded open model and chat with it in the terminal.
- Add Open WebUI if you want a nicer interface, or point your existing tools at Ollama's local API.
- Only then decide whether you need bigger hardware.
See the full AI & local-LLM list, and if you also use the big cloud models, the guide on managing Claude & ChatGPT.
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