How to Run an LLM Locally, the Quick Version
Short answer: To run an LLM locally, install the free Ollama app, then run one command — ollama run gemma3:12b — to download and chat with Google’s Gemma model. It works on Windows, macOS, and Linux, needs about 16GB of RAM, and runs fully offline.
Running a large language model on your own computer is easier than it sounds. With a free tool called Ollama and one of Google’s open Gemma models, you can run an LLM locally in about ten minutes — no cloud, no subscription, and nothing leaving your machine.
In plain terms: install Ollama, run one command to download Gemma, and start chatting. Below, each step is laid out clearly, and we then help you pick the right model for your computer.
What You Need to Run an LLM Locally
You don’t need a workstation. To run an LLM locally at a usable speed, aim for this:
- RAM: 16GB minimum, 32GB for comfort. More RAM means bigger models.
- GPU / VRAM (optional but much faster): an NVIDIA GPU with 8GB+ of VRAM helps a lot, and 24GB runs large models. On a Mac, the unified memory does the same job — a 32GB+ Apple silicon Mac is excellent.
- Storage: a few GB of free space per model.
- Software: Ollama and a Gemma model — both free.
A cheap mini PC with 32GB of RAM is genuinely enough to run an LLM locally at conversational speed. A dedicated GPU is what helps most if you want more headroom.
How to Run an LLM Locally with Gemma and Ollama
Here is the whole process, step by step.
Install Ollama
Download Ollama from ollama.com for Windows or macOS and run the installer. On Linux, install it straight from the terminal:
curl -fsSL https://ollama.com/install.sh | shDownload and run Gemma
Open a terminal (or the Ollama app) and run the command below. The first time, it downloads the model — a few GB — then it starts instantly and you chat right there. Type /bye to exit.
ollama run gemma3:12bPick a model that fits your machine
Got 16GB of RAM or a weaker GPU? Use a smaller model. Got 24GB+ of VRAM or a 64GB+ Mac? Go bigger. Just swap the size to match your hardware:
ollama run gemma3:4b # lighter, very fast
ollama run gemma3:27b # heavier, smarterAdd a chat window (optional)
Prefer a nicer interface than the terminal? Install Open WebUI to chat in your browser, or use LM Studio for a point-and-click app. Both are free and run the same local models.
Which Gemma Model Should You Run?
Gemma comes in several sizes, so the best LLM to run locally depends on your memory. A rough guide:
- gemma3:1b / gemma3:4b — great on 8–16GB machines and laptops without a strong GPU. Fast, and fine for everyday chat, writing, and coding help.
- gemma3:12b — the sweet spot for 32GB of RAM or a 16–24GB GPU. Clearly smarter.
- gemma3:27b — for 24GB+ of VRAM or a 64GB+ Mac. The most capable, but slower on modest hardware.
If a model feels slow or runs out of memory, drop to the next size down. That one change fixes most problems when you run an LLM locally.
Tips to Run an LLM Locally Faster
A few tweaks make local models noticeably smoother:
- Match the model to your memory. A model that fits in VRAM or RAM runs fast; one that doesn’t will crawl.
- Use the default (quantized) builds. Ollama’s Gemma models are already compressed, which is why they fit on normal machines.
- Close memory-hungry apps — especially browsers with many tabs — before loading a big model.
- Let the GPU help. On NVIDIA machines Ollama uses the GPU automatically, so keep your drivers up to date.
- Tidy up with ollama rm <model> to remove models you no longer use and free disk space.
Want More Than How to Run LLM Locally?
Want to go further? See how a Google Gemma AI mini PC runs a private assistant for around $300, and if you need more power, our best GPU for AI guide covers the cards that make local models fly. You can also grab Ollama free from ollama.com.
Frequently Asked Questions
Can I run an LLM locally?
Yes. With a free tool like Ollama and an open model like Gemma, any computer with about 16GB of RAM can run an LLM locally. A GPU makes it faster, but it is not required.
How do I run an LLM locally?
Install Ollama, then run one command such as ollama run gemma3:12b. Ollama downloads the model the first time and then lets you chat in your terminal. It works on Windows, macOS, and Linux.
What LLM can I run locally?
Many open models run locally, including Google’s Gemma, Meta’s Llama, Mistral, and Qwen. Gemma is a great starting point because it is small, fast, and free. Just pick a size that fits your memory.
Is it free to run an LLM locally?
Completely. Ollama and the Gemma models are free and open source, and there are no per-message fees. Your only cost is hardware you most likely already own.
How much RAM do I need to run an LLM locally?
16GB is the realistic minimum for small models; 32GB runs mid-size models like Gemma 12B comfortably. For the largest models, you want 24GB+ of GPU VRAM or a 64GB+ Apple silicon Mac.
What is the best LLM to run locally?
There is no single winner, but Gemma 3 (4B or 12B) is one of the best LLMs to run locally for most people: fast, capable, and free. Match the size to your hardware for the smoothest experience.