Open weights model licences: what Mistral Large 4 means for marketing teams
An open weights model is not always free to use as you like. What Mistral Large 4's new licence allows, how others compare, and four checks before you build.
By overads Inc., the team building gloofy
An open weights model is one whose trained parameters you can download and run yourself, but open weights does not mean you can do anything with it: the licence decides that. Mistral made the point this week by releasing Mistral Large 4, about a trillion parameters, under a modified MIT licence that is free for most uses and requires a separate commercial licence if you offer the model as a service. For a marketing team, that distinction rarely bites. For an agency or a software company, it can.
What Mistral released this week
Mistral previewed Large 4 through its API on 6 October and published the weights on 29 October. The model card describes about 1 trillion total parameters in a mixture-of-experts design, about 52 billion of them active per token, a one-million-token context window, and text and image input. Mistral's own benchmark claims are mostly about coding and security, not marketing, and we have not measured it.
This is not a laptop model. The reference setups on the model card use a single node with eight GPUs. According to one independent write-up, the weights take roughly 1 TB in full 8-bit format and roughly 500 GB in the 4-bit version. Marketing teams are more likely to meet it through a hosted provider or an internal platform team than on their own machines.
Is an open weights model the same as open source?
Not usually. Open source software means you get the code and the right to use it freely. With a model, you get the weights, often without the training data or code that produced them, and the licence sets the conditions. Some, like Apache 2.0, have almost none. Others add limits by revenue, by size of user base, or by what you do with the model.
| Model | Licence | Main condition for a business |
|---|---|---|
| gloofy-1-nano, gloofy-14b | Apache 2.0 | Keep the licence and notices |
| Mistral Large 4 | Mistral Ecosystem Open-Weight License (modified MIT) | A separate commercial licence if you offer it as a service to third parties; internal use is exempt |
| LFM2.5-24B-A2B | LFM Open License v1.0 | Free commercial use below USD 10 million annual revenue; above that, a separate licence |
| Models built on Llama 3.1 | Llama 3.1 Community License | Naming and attribution rules, an acceptable use policy, and a separate grant above 700 million monthly users |
What Mistral's Model-as-a-Service rule means for marketers
The licence defines Model-as-a-Service as giving a third party access to the model, for inference or further training, in a way that gives them meaningful control over inputs, parameters or training data. Reading the licence text, here is how that applies to typical marketing setups. This is our reading, not legal advice.
- An in-house team running it internally: exempt. Internal use, where the model is not made available to third parties, does not trigger the rule.
- A product with AI inside a specific feature: excluded. The licence carves out end-user products where the model's capabilities are embedded in specific features, such as a button that writes a headline.
- A tool that only relays requests to a model hosted elsewhere: excluded.
- An agency or software company giving clients an open prompt box on the model: likely in scope, because the client controls the inputs. Ask Mistral.
The rule also reaches affiliates and fine-tuned derivatives, so adapting the model does not take you outside it. The licence sets no revenue threshold, unlike Liquid AI's, so a small company offering the model as a service needs the same commercial licence as a large one.
Four licence checks before you build on an open weights model
- Read the licence file in the repository. Headlines say "open"; the file says what you can do. Names such as "modified MIT" need reading to the end.
- Check three thresholds. Your annual revenue, your monthly users, and whether third parties get to control the model. Check clients too, if you are an agency.
- Check derivatives. Find out whether conditions follow your fine-tuned version and what attribution you owe. Adapters and merged models usually inherit them.
- Record the version. Save the licence text you accepted with the date, since terms can differ between releases of the same family.
Do you need a trillion-parameter model for marketing?
For most marketing work, no. When we measured model size on marketing tasks, 8 billion parameters bought nothing over 4 billion, and later 14 billion added only 0.008 on the same exam. On exam v3.3 of our public marketing benchmark, which scores 150 real published ads by exact label match, the 675B Mistral Large 3 scores 0.825 and our released 14B adapter 0.816, tied within measurement error. That is one narrow task, tagging ads, and it says nothing about strategy or reasoning, where larger models are better. Mistral Large 4 has not been measured on it.
The practical point is to match size to the job, as we set out in our comparison of the best LLM for marketing. A larger model costs more to run and rarely improves a task that is already narrow.
Where gloofy fits, and where it does not
gloofy-1-nano and the gloofy-14b adapter are released under Apache 2.0, listed under the gloofy models, so you can use them commercially, change them and ship them in your own product without asking us. That simplicity is a real advantage for agencies, and it is the only way we claim to beat larger models here.
They are not substitutes for a frontier-scale model. They do not reason broadly, they have no vision input and they will not help with coding or research. If you need those, a larger open weights model or a hosted API is the right tool, and our marketing LLMs and open models hub collects more on choosing one.
What to do this week
- List every open model your team or vendors use, with its licence.
- If you are an agency, write down who controls the prompts in anything clients touch, and ask a lawyer about it.
- Save a copy of each licence with the date you adopted it.
- Before adopting a larger model, score it against your smaller option on 50 real examples.
FAQ
What is an open weights model?
An open weights model is one whose trained parameters are published for anyone to download and run on their own hardware. It differs from open source software because the training data and code are often not included, and the model's licence, not the word open, decides what you may do with it.
Is Mistral Large 4 free for commercial use?
Largely yes. The Mistral Ecosystem Open-Weight License, a modified MIT licence, allows commercial use and fine-tuning. If you or an affiliate offer the model as a service to third parties, you need a separate commercial licence from Mistral first. Internal use is exempt, and the licence states no revenue threshold.
Can a marketing agency use Mistral Large 4 for clients?
It depends on what clients control. Using it internally to produce client work appears exempt, and embedding it in a specific product feature is excluded. Giving clients open access where they control inputs or parameters likely counts as Model-as-a-Service. This is our reading, not legal advice, so check with Mistral or a lawyer.
What is the most permissive licence for open models?
Apache 2.0 is among the most permissive common licences: you can use, change and sell what you build, and the main duty is keeping the licence and notices. gloofy-1-nano is released under it. Always read each model's licence file, since families can change terms between releases.