Getting Started with Local AI in 2026

Short answer: Install Ollama, run ollama run qwen3:30b, install Open WebUI for a ChatGPT-like UI, and you have local AI working in 10 minutes. The rest of this guide is everything else you'll want to know after that.

This is a hub page. It links into every major area of the directory. Bookmark it.

The 30-second mental model

Local AI has three independent layers:

1. Model - the actual weights (Qwen3, Llama, Mistral, etc.)
2. Inference engine - what loads and runs the model (Ollama, LM Studio, vLLM, llama.cpp)
3. UI / orchestration - what you actually interact with (Open WebUI, AnythingLLM, n8n, or your own code)

Mix and match. Ollama + Open WebUI is the common starting combo. Ollama + AnythingLLM is the RAG starting combo. Ollama + n8n is the automation starting combo.

Step 1 - pick a model that fits your hardware

The single biggest gotcha for newcomers is picking a model their GPU can't actually run. Use our VRAM calculator, or use this cheat sheet:

See our /best/ pages for task-specific picks (coding, RAG, agents, image-gen).

Step 2 - install Ollama

For 95% of newcomers, Ollama is the right starting point. One command:

macOS / Linux:

curl -fsSL https://ollama.com/install.sh | sh

Windows: download the installer from ollama.com/download.

Verify:

ollama run qwen3:30b

(Pick a tag from the table above that fits your hardware.)

That's it - you have a local LLM. Type questions, get answers, type /bye to exit.

Step 3 - install a UI

Terminal chat is fine for testing. For actual use you want a real interface:

• Open WebUI - looks like ChatGPT, multi-user. Best general pick.
• AnythingLLM - best if you want document chat / RAG out of the box.
• LM Studio - desktop app, alternative to Ollama + Open WebUI in one.

Open WebUI in one command:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway \
  -v open-webui:/app/backend/data --name open-webui \
  ghcr.io/open-webui/open-webui:main

Visit http://localhost:3000, sign up (first user becomes admin), and Ollama auto-discovers.

Step 4 - pick your next 5 things

Once chat works, pick the next direction based on what you actually want:

Document chat / RAG

Add AnythingLLM (or use Open WebUI's RAG feature). Drag PDFs in, ask questions, get cited answers.

Image generation

Install ComfyUI. Download a Flux Dev or SDXL checkpoint from HuggingFace. Drop a workflow JSON from civitai onto the canvas. Generate.

Automation / agents

Install n8n. Build a workflow: webhook → Ollama node → response. Now you have a private AI API.

Code assistant

Use Continue.dev (VS Code extension) pointed at Ollama running a code-tuned model like Qwen3-Coder or DeepSeek-Coder V3.

Step 5 - when to upgrade hardware

You'll know it's time when:

• You want bigger models than fit (jump to /calculator/vram to see what next-tier GPU buys you)
• You want to serve a team (jump to vLLM and multi-GPU)
• You hit thermal/power limits

Use our cost-vs-cloud calculator to confirm the upgrade pays for itself vs continuing to use cloud APIs.

Frequently asked

Do I need an NVIDIA GPU?

No. Apple Silicon (M2/M3/M4) works great via MLX. AMD GPUs work via ROCm with Ollama. Intel Arc works for inference. But NVIDIA has the best ecosystem support.

Will local AI replace ChatGPT for me?

For most tasks (chat, drafting, summarization, coding assistance, RAG over your own docs), yes - open-weight 30B+ models in 2026 are GPT-4-class. For frontier reasoning, agentic web browsing, and creative writing at the very top, frontier closed models still lead.

Is my data really private with local AI?

Yes, if your model and UI run on hardware you control with no telemetry to the internet. Verify by blocking the host with a firewall and confirming responses still come back.

How much electricity does this use?

A 4090 at 8 hrs/day load is ~$16/month at US average rates. See our cost calculator.

What's the catch?

You're responsible for: hardware purchase, occasional driver updates, model selection, troubleshooting. There's no support team. The community (r/LocalLLaMA, Discord) is your support.

Where to go next

• Browse all tools
• Browse all models
• Browse all hardware
• Best LLM for coding · Best for RAG · Best for agents
• VRAM calculator · Cost vs cloud calculator