In 2025, the ability to run large language models (LLMs) entirely on your local machine has become easier than ever. Whether you’re a developer, data scientist, researcher, or tech enthusiast, running models like Llama 3 locally offers unmatched privacy, control, and performance—without relying on cloud services. In this guide, we’ll walk you through setting up Llama 3 using Ollama, a free and powerful tool that simplifies the process. You’ll learn how to install models, set up a user-friendly interface, and ensure your system meets the hardware requirements.
Step 1: Download and Install Ollama
First, you’ll need to install Ollama, a free app that makes it easy to run LLMs locally.
- Go to https://ollama.com
- Download the version for your operating system (macOS, Windows, or Linux).
- Install it like any regular app.
- macOS/Linux: Just run the installer and move it to your Applications folder.
- Windows: Ollama will require Docker (more on that below).
- Launch Ollama and follow the prompts to install command line tools if prompted.
Step 2: Install Llama 3
Once Ollama is installed, use your terminal to download and run Llama 3.
Open your Terminal (or Command Prompt on Windows), then run:
ollama run llama3
This will download and launch the default Llama 3 8B model. You can start chatting with it immediately after the setup completes.
Step 3: Install Specific Model Variants
Llama 3 is available in multiple sizes. Here’s how to install them:
| Model | Command | Notes |
|---|---|---|
| Llama 3 8B | ollama run llama3:8b | Great for most local tasks |
| Llama 3 70B | ollama run llama3:70b | Needs serious hardware |
⚠️ Note: There is no official 45B variant from Meta. If you see a 45B model, it’s likely a community-merged version.
Step 4: Install Docker (Windows Only)
macOS and Linux users can skip this step.
If you’re using Windows, Ollama runs inside a Linux container, so you’ll need Docker:
- Download Docker from https://www.docker.com
- Install it and start Docker Desktop.
- Ensure Docker is running before using Ollama.
Step 5: Set Up the Open Web UI (Optional but Recommended)
For a cleaner experience with a graphical interface, try Open Web UI, a local frontend for Ollama.
- Visit the GitHub repo: https://github.com/open-webui/open-webui or https://docs.openwebui.com/getting-started/
- Follow the setup instructions for your platform.
- Once installed, run the startup command (usually via Docker).
- Open your browser and go to http://localhost:3000 to interact with models via a GUI.
Hardware Requirements
Running large models requires decent hardware. Here’s a general breakdown:
| Model | RAM | GPU VRAM | Notes |
|---|---|---|---|
| Llama 3 8B | 16–32 GB | 8–24 GB | Consumer-grade GPUs supported |
| Llama 3 70B | 128–192 GB | 80 GB+ | Needs enterprise GPUs (e.g. A100) |
Tip: You can ask tools like ChatGPT to analyze your system specs and compare them to these requirements.
Final Thoughts
Running Llama 3 locally offers speed, privacy, and control—no need to rely on external servers. Whether you’re coding, analyzing data, or generating content, having local models puts powerful AI right at your fingertips.
Try different models from the Ollama library: https://ollama.com/library