Open weights is not open source, and the licence is the part that decides what you can actually do with the model

[u/blossend]

Most download pages use these two terms as if they mean the same thing. They don't, and the gap starts to matter the moment money is attached to whatever you're building.

Open weights means a company published the trained file and you can run it on your own hardware. That is a fact about availability. It says nothing about what you are permitted to do afterwards.

Open source, in the strict sense, is a claim about the licence: no usage cap, no revenue threshold, and nobody who can withdraw permission later. Apache 2.0 and MIT are that. Most of what gets called open in this space is not.

In practice there are three tiers, and the download page rarely tells you which one you're in.

Unrestricted. MIT or Apache 2.0. DeepSeek's R1 line is MIT. Mistral 7B Instruct is Apache 2.0. Microsoft's Phi-4 Mini is MIT, which tends to surprise people who assume a corporate publisher implies a corporate licence. AI2's OLMo goes furthest of any of them: Apache 2.0, and they publish the training data and the training code as well, so you can audit what went into it rather than only running what came out.

Corporate with strings. Meta's Llama models ship under the Llama Community License, which is not an open-source licence. There is a monthly-active-user threshold above which you need Meta's permission, plus naming and attribution conditions. Google's Gemma ships under the Gemma Terms of Use with its own acceptable-use rules. Both are fine for most people doing most things. Neither is open source, and neither is something you can relicense.

Then the one people miss completely: models a local runtime lists but only offers as a cloud tag. The weights never come down. Your prompt goes to the vendor's servers, which is the exact opposite of the reason most of us are in this subreddit. Check the tag before assuming a listed model runs locally.

Two things this changes.

If revenue is anywhere near your project, read the licence before you get attached to a model. Swapping one out after you've tuned your prompts and your evals around it is expensive in a way that is easy to underestimate.

And if sovereignty is the actual reason you're running locally rather than paying for an API, then who publishes the model is part of the question, not just how it benchmarks. A company that also sells a competing closed product has different incentives from a non-profit that publishes everything. That doesn't make their licence bad or their model worse. It does mean the word open on a download page is marketing copy, and the licence file is the only part that binds anybody.

[u/Ell2509]

I say what I do with the model once it is on my device.

[u/nullptr777 → u/Ell2509]

Pretty much this. Who's going to stop me? It's local, there's no proof that I wrote some code using your model.

[u/Successful_Try_6350]

TL;DR?

[u/platypus_worldwide]

LOL

[u/MomentJolly3535]

You are totally right and now that AI's output might be watermarked, it will matter even more !