Chapter Zero · Beginner FAQ

Does an “Open-Source Model” Mean It's Free?

Q: Does an “Open-Source Model” Mean It's Free?

Most “open-source models” only publish the weights — the trained brain itself. Training data and training methods usually stay closed. Download costs nothing, but running it needs a GPU and electricity, and making money with it still depends on the license.

The news says a model has been "open-sourced," and the comments cheer "top-tier AI, free to use." Hold the celebration. In AI, "open source" and the free you have in mind are several layers apart. This page peels them one by one.

One-sentence answer

Most "open-source models" only publish the weights — the trained brain itself. Training data and training methods usually stay closed. Download costs nothing, but running it needs a GPU and electricity, and making money with it still depends on the license.

First, a correction · "Open source" in AI is a bit special

Open source in software means you get the source code: you can see every line, change it, compile it yourself. The whole recipe is on the table — ingredients, method, heat, all of it.

"Open-source models" in AI are rarely that generous. What you get is the weights: hundreds of gigabytes of numbers — the finished pot of soup after it's been stewed. You can drink the soup, but the recipe (training data) and the method (how it was trained) usually stay secret. The more precise name inside the field is "open weights." News headlines just don't bother to tell them apart.

And don't forget the license. An open-source model comes with a usage agreement: some allow any commercial use, some restrict the purpose or how many users you have. Playing on your own is basically fine; read it before you make money with it. A lot of people skip this step. The cost of skipping it can be a lawyer's letter.

The three-piece checker · what did they actually open

To judge how open a model really is, three things are enough: weights, data, method. Tap the two buttons below and see how many lights each typical case turns on.

Model weights

Training data

Training method

Full-size vs. distilled · the one in the news and the one on your computer may be two models

Another common mix-up: the "full-size" model topping the leaderboards in the news, and the one you actually run on your own computer, are usually two different things. Companies typically "distill" a large model into a small one: the big one teaches, the small one learns. Some ability stays; the size shrinks by tens of times. Tap the button below to see the comparison.

Full-size version

The one topping the charts in the headlines

Size (parameters)Hundreds of billions

AbilityWhere the leaderboard scores come from

🏢 Hardware needed: a roomful of servers, a row of pro GPUs, the electricity meter spinning like a fan

Distilled version

The one that actually runs on your computer

Size (parameters)Tens of billions

AbilityFine for daily use, flinches on hard problems

💻 Hardware needed: one well-specced computer, a decent GPU, a slightly louder fan

See it now? What you run locally is usually the small one. It's fine at chat, summaries, and email — but if you hold it to the leaderboard scores from the news, it'll feel hard done by. Before you praise a model, check which version you're actually using.

Want to run it on your own computer · what you need

"Free to download" and "free to run" are two different things. The model file itself costs nothing, but running it eats VRAM: the bigger the model, the more expensive the GPU you need. Past a certain size, one card isn't enough — you need several at once. Electricity is an ongoing cost too. At home it probably won't sting; at server scale it's a real bill.

How big a model can your own computer actually run? No need to guess — this site has a ready-made VRAM calculator. Enter your GPU model and it tells you straight. Stay within your means. Not being able to run the full-size version is nothing to be ashamed of — a small model with tens of billions of parameters is already quite capable at everyday work.

✅ What this page wants to share with you

Most "open source" is just open weights: you get the soup, the recipe and the method stay secret. The precise name is "open weights"
Free to download and free to run are two different things: running it costs a GPU and electricity — the bigger the model, the thicker the bill
What you run locally is usually a distilled small one: the full-size version in the news lives in a data center. Don't hold the small one to leaderboard scores
Read the license before commercial use: play on your own as you like; read the agreement before you make money with it