A little over a year ago, I suggested it might be too soon to run AI models locally. The field has moved quickly since then. Today, I think it’s time to start experimenting with open-source AI models on your own computer.
The AI Sandbox Metaphor
In recent posts, I explained a bit about what is in an AI model and the components that make it work.
Think of ChatGPT as OpenAI’s sandbox. The model itself, the billions of mathematical parameters, lives in their data centers. The website is just the carefully fenced-in playground where you’re allowed to interact with it. The rules, the guardrails, and even how long it remembers you. All of that is controlled by OpenAI.
When you run AI locally, you’re building your own sandbox in your own backyard. You choose:
- What goes in : Which AI model you load
- What comes out : Where your conversations are stored (or not)
- Who plays : Who has access to your sandbox
- How big it is : How much computer power you dedicate
Using ChatGPT or Claude online is like sending your questions across town to someone else’s playground. Running locally means setting up a private sandbox right next to your desk.
What Actually Happens When You Run AI Locally
When you download and launch a model, here’s what changes:
- You host it. Your computer becomes the model’s new home. The parameters live in your memory, not a distant server farm.
- Your machine does the math. Every question triggers billions of calculations. Your CPU/GPU ramps up, fans spin, and the sandbox comes alive.
- You set the rules. You decide what information the AI sees, what it produces, and whether it connects to the internet or stays fully offline.
The Three Resources Your Sandbox Uses
Running AI locally comes down to three main ingredients:
- Electricity (energy to play). Every answer consumes power, about the same as gaming or streaming video. You can even track this and compare efficient vs. power-hungry models.
- Memory and processing (sandbox size). Bigger models need more RAM and faster processors. A small sandbox slows things down; a big one lets the AI move faster.
- Internet (optional window). You decide if your sandbox is sealed off (offline mode) or has a window to the world (online mode).
Why Building Your Own Sandbox Matters
- Privacy by design. Conversations never leave your machine.
- Learning by doing. You can test power use, memory needs, and offline/online behavior.
- Clear costs. No mysterious cloud bills, just electricity usage you can measure.
The Trade-offs
What you gain: privacy, control, transparency, and offline capability.
What you give up: convenience, speed, automatic updates, and access to the most powerful cloud models.
Your AI, Your Rules
Running AI locally is like moving from renting time in someone else’s playground to owning your own sandbox. You control the toys, the space, and the rules.
In the next post, I’ll show you how to download and run your first local model using LM Studio, your starter kit for building a personal AI sandbox.
Your backyard is about to get a lot more interesting.