The short answer
A closed model runs only on the provider's computers and you reach it through their service. An open-weights model can be downloaded and run by anyone. That mostly matters for privacy, cost at scale and control. For everyday personal use, the difference is usually smaller than the argument about it.
Open weights is not open source
The weights are the numbers the training produced — the model itself. When a company releases them, anyone can download and run the model on their own machines.
That is not the same as open source in the traditional sense. The training data is almost never released, the training code often is not, and many licences restrict commercial use. You get the finished thing, not the recipe.
So a model can be called open while remaining impossible to reproduce, inspect fully, or use freely for business. The word is doing a lot of work.
DOT / THE TRANSLATOR
Open weights means you can have the cake. Open source would mean you could have the recipe, the oven, and the name of the farm the eggs came from.
What it actually changes
Three things, in practice, and only one of them is the argument people have online.
Where the difference shows
- Privacy
- Running it yourself means your text never leaves your equipment. This is the strongest argument.
- Cost at volume
- Paying for hardware can beat paying per token, once volume is high and steady.
- Control
- Nobody can change, price up or withdraw a model you already hold.
- Capability
- The best closed models are usually ahead, though the gap has narrowed and moves constantly.
The shape of the trade rather than a scorecard. Which side leads on capability changes from month to month.
When it matters to you
If you are one person asking an assistant to draft emails, it probably does not. You will get a better experience from a good closed product, and the privacy question is better answered by what you choose to paste.
It starts to matter when the material cannot leave the building — health records, legal files, anything under a contract that forbids it. Then running a model yourself stops being ideology and becomes the only lawful option.
It also matters if you are building something on top of a model. Depending on a service you do not control is a real business risk, and people who lived through a sudden price change tend to feel strongly about it afterwards.
What to actually do
- For personal use, choose on quality and terms rather than on openness.
- If data cannot leave your premises, look at open weights first.
- If you are building a product, ask what happens when the model you depend on changes.
- Read the licence before commercial use. Open does not reliably mean free to sell with.
See it for yourself
Reading about it only gets you so far. This one is written to show you the thing described above, rather than describe it again.
If I wanted to stop sending my work to somebody else's computer, what would I actually have to do, step by step, and what would I be giving up by doing it?
Then paste it into whichever assistant you use — ChatGPT, Claude, Gemini or Copilot. Not sure which? Meet them all.
If you remember nothing else
- Open weights means you can download and run it. It rarely means open source.
- Training data and code are usually withheld, and licences often restrict business use.
- The real benefits are privacy, control, and cost once volume is high.
- For ordinary personal use the difference is smaller than the argument suggests.
- If your material cannot leave the building, this is the option worth exploring.
Where this came from
- Open Source Initiative, The Open Source AI Definitionchecked 26 September 2026
Anything here that turns out to be wrong is worth telling us about. Figures that move — prices, sizes, energy use — are kept in the registry with their dates, rather than written into the prose where they would quietly go stale.
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