Local LLMs: How to Run Llama 3 and DeepSeek on Your Own Hardware

While cloud-based AI models like Gemini and ChatGPT are powerful, they come with strings attached: subscription fees and data privacy concerns. For developers and privacy enthusiasts, 2026 is the year of Local LLMs.

Why Go Local?

Running a model like Llama 3 or DeepSeek locally on your machine means:

1. Total Privacy: Your prompts and code snippets never leave your computer.
2. No Internet Required: You can code or write on a plane or in a remote cabin.
3. Uncensored Access: You control the system prompts and parameters.

What Hardware Do You Need?

To run a decent quantized model (7B or 8B parameters) smoothly, you don’t need a supercomputer. A modern GPU with at least 8GB or 12GB of VRAM (like an NVIDIA RTX 3060 or 4070) handles these models surprisingly well. For Mac users, the M3 and M4 chips with unified memory are beasts for local inference.

Tools to Get Started

• LM Studio: A user-friendly interface that lets you download and chat with models in one click.
• Ollama: A powerful command-line tool for Linux and Mac users to spin up models instantly.

Conclusion

The democratization of AI isn’t just about using it; it’s about owning it. By running local models, you take control of your data, your costs, and your creative freedom. The future of AI is decentralized, and it starts on your own hardware.