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How to run AI locally: your first model in ten minutes

Install Ollama, run one command, and chat with an open model on the computer you already own. No account, no cloud, no monthly bill.

Updated Oct 26, 2026 · RunItLocal.io

Running an AI model on your own computer takes one download and one command. Nothing you type leaves your machine, there's no subscription, and it keeps working with the internet off.

This guide gets you from nothing to a working chat in about ten minutes. Most of that is the model downloading.

What you need

  • A computer from the last six or seven years. A gaming PC, a Mac with Apple silicon (M1 or newer), or a laptop with 16 GB of memory all work.
  • About 5 GB of free disk space for your first model.
  • A graphics card helps but isn't required. With one, answers come faster than you can read. Without one, small models still run on the processor, just slower.

Not sure what your machine can handle? The homepage reads your GPU in the browser and shows which models fit.

Step 1: Install Ollama

Ollama is a free app that downloads models and runs them for you. It handles the hard parts: picking a file size that fits, using your graphics card, and keeping the model loaded between questions.

  • Mac and Windows: download the installer from ollama.com and run it.
  • Linux: paste this into a terminal.
curl -fsSL https://ollama.com/install.sh | sh

Step 2: Run your first model

Open a terminal (Terminal on Mac, PowerShell on Windows) and run:

ollama run qwen3:8b

The first run downloads about 5 GB. After that it starts in seconds. When you see a >>> prompt, type a question and press Enter. Type /bye to quit.

Qwen3 8B is our default first model: good at writing, chat and light coding, and small enough to run fast on an 8 GB graphics card. If your machine has less memory, or no graphics card, start smaller:

ollama run qwen3:4b

Step 3: Check it's using your GPU

While a model is loaded, run this in a second terminal:

ollama ps

The PROCESSOR column should say 100% GPU. If it says something like 48%/52% CPU/GPU, the model is too big for your graphics memory and part of it runs on the much slower processor. Pick a smaller model, or read how much VRAM you need.

What to expect

Speed is measured in tokens per second. A token is about three quarters of a word. Around 10 tok/s is reading speed; 30 tok/s and up feels instant.

Here's what a common starter card, the RTX 3060 with 12 GB, can run, from our calculator:

RTX 3060, 12 GB · estimated with our calculator · full page

  • Qwen3 4BQuick everyday chat and summaries
    ~79 tok/s
    Runs greatqwen3:4b
  • Qwen3 8BA solid all-rounder for chat and writing
    ~38 tok/s
    Runs greatqwen3:8b
  • Gemma 3 12BReads images as well as text
    ~24 tok/s
    Usablegemma3:12b
  • Qwen3 14BNoticeably smarter at reasoning and code
    ~21 tok/s
    Usableqwen3:14b
  • gpt-oss 20BOpenAI's open model. Fast, strong reasoning
    needs 16 GB
    Too biggpt-oss:20b
  • Gemma 3 27BGoogle's best open model for its size
    needs 19 GB
    Too biggemma3:27b
  • Qwen3 30B-A3B30B smarts at small-model speed
    needs 21 GB
    Too bigqwen3:30b
  • Qwen3 32BStrong coding and long answers
    needs 22 GB
    Too bigqwen3:32b
  • Llama 3.3 70BClose to the big cloud models
    needs 45 GB
    Too bigllama3.3:70b
  • gpt-oss 120BOpenAI's largest open model
    needs 67 GB
    Too biggpt-oss:120b
  • Qwen3 235B-A22BAlibaba's flagship open model, for multi-GPU rigs
    needs 144 GB
    Too bigqwen3:235b
  • DeepSeek R1 671BThe full DeepSeek R1, for the biggest rigs
    needs 406 GB
    Too bigdeepseek-r1:671b

Every GPU we track has its own page like this one. Start at every GPU.

Where to go next