How to Check an AI Model's License
Downloadable weights are not the same as permission to use a model in your product. This guide is a review checklist for working out whether an open-weight or open-source model can be used commercially — how to find the real license, tell true open source from a source-available community license, and catch the governance gotchas that bite later: acceptable-use clauses, redistribution and derivative rules, and output ownership. It is not legal advice.
In plain words
Checking an AI model's license means finding the authoritative license text, identifying whether it is true OSI-approved open source (like Apache-2.0 or MIT) or a source-available community license (like Llama or Gemma), and then reading it for the conditions on commercial use — and PlayCISO has a free, browser-based model license checker to start that lookup. "Open weights" describes availability, not your rights.
The gotchas that matter are rarely the headline "commercial use allowed": they are acceptable-use clauses, scale thresholds, redistribution and derivative rules, and output ownership. Record the decision in your AIBOM and get legal sign-off on anything ambiguous. This is a review checklist, not legal advice.
Step by step
- 1
Find the actual license, not the marketing
A model being on Hugging Face or called "open" tells you nothing about your rights. Find the authoritative license text: the model card's license field, the LICENSE or LICENSE.txt file in the repo, and any linked acceptable-use policy or community-license PDF. Note the exact model and version — licenses differ between a base model and its fine-tunes, and between major versions. Save a copy of the license as you found it, with the date.
- 2
Identify the license type
Decide which bucket it falls in. True open-source licenses (Apache-2.0, MIT, BSD) are OSI-approved and place no restrictions on who uses the model or for what. Source-available or "community" licenses — Llama's Community License, Gemma's Terms, Falcon's earlier terms — ship the weights openly but add use restrictions, so they are not open source in the OSI sense. "Open weights" describes availability, not the license. Research-only or non-commercial licenses (some CC-BY-NC releases) bar commercial use outright.
- 3
Check commercial-use permission and any thresholds
Confirm the license actually grants commercial use, then read for conditions attached to it. Some community licenses add scale triggers — for example a user- or revenue-count threshold above which you must request a separate license. Check whether use inside a product you sell, use by your customers, or use to train or improve a competing model is permitted or carved out. If the license is silent or ambiguous on your intended use, treat that as unresolved, not as permission.
- 4
Read the acceptable-use policy
Many model licenses incorporate an acceptable-use policy (AUP) by reference, and breaching it can terminate your license. Read it for prohibited domains and behaviours — things like generating certain regulated content, specific high-risk uses, or uses that violate third-party rights — and compare them against what your application will actually do. An AUP that forbids your core use case is a hard stop regardless of whether "commercial use" is otherwise allowed.
- 5
Check redistribution, derivative and fine-tune terms
If you will share the model, a quantized version, a fine-tune, or merged weights, check what the license requires: passing the same license and AUP downstream, including attribution or a notice file, naming conventions for derivatives (some require the original model name in your model's name), and whether outputs may be used to train other models. Some licenses restrict distributing derivatives at all, or require you to make the license text available to your own recipients.
- 6
Check output ownership and attribution
Separate the license on the weights from your rights to the text, code or images the model generates. Most permissive and community licenses do not claim ownership of your outputs, but some add attribution or notice obligations, or disclaim that outputs may not be protectable or may resemble training data. Confirm who owns the outputs, whether any attribution is required when you publish them, and whether the license disclaims warranties and indemnity for what the model produces.
- 7
Record it in your AIBOM and get legal sign-off
Log the model, version, license name and type, commercial-use decision, any thresholds, the AUP link and the date you reviewed it in your AI Bill of Materials so the determination is auditable and re-checkable when the license changes. Route anything ambiguous — unclear commercial rights, a threshold you might cross, a derivative or redistribution plan — to legal for a real sign-off. This checklist is a review aid, not legal advice; a lawyer makes the call on anything that matters.
Look up a model, see its license type and whether it is OSI-approved open source or a source-available community license, and get the commercial-use and redistribution flags to review — free, in your browser.
Related
The lookup tool this guide walks you through — license type, commercial-use and redistribution flags for a model.
AIBOM validatorValidate an AI Bill of Materials so your recorded model-license decisions are complete and auditable.
How to build an AI Bill of MaterialsWhere to record each model, its license, and the commercial-use determination so it survives an audit.
How to audit a machine learning model fileInspect the model file itself for safety and provenance alongside the license review.
Frequently asked questions
Is "open" the same as "open source"?
No. "Open" and "open weights" usually mean the weights are freely downloadable, which is about availability, not your legal rights. "Open source" has a specific meaning — an OSI-approved license (like Apache-2.0 or MIT) with no restrictions on who uses the software or for what. Many popular "open" models ship under source-available or community licenses that add use restrictions, so they are not open source even though you can download them freely.
Can I use Llama or Gemma commercially?
Generally yes, within the limits of their community licenses — but you must verify against the current license text, which can change between versions. These are source-available community licenses, not OSI open source: they permit commercial use while adding conditions such as acceptable-use policies, redistribution and naming requirements, and in some cases scale-based thresholds above which you need a separate license. Read the license for the exact model and version you plan to ship, and get legal sign-off if your use is large-scale or ambiguous. This is not legal advice.
What's a source-available license?
A source-available (or "community") license makes the code or model weights openly available to download and use, but attaches conditions that an OSI-approved open-source license would not — for example restrictions on certain uses, scale thresholds, redistribution or derivative rules, or an acceptable-use policy. The weights being downloadable does not make the license open source; the restrictions are what put it in the source-available category.
Do I own the outputs a model generates?
Usually the license on the weights does not claim ownership of what you generate, but you should confirm it per license rather than assume. Some community licenses add attribution or notice obligations when you use or publish outputs, disclaim warranties, or note that outputs may not be protectable or could resemble training data. Treat output rights as a separate question from your right to run the model, and check both.
Where should I record a model license decision?
In your AI Bill of Materials (AIBOM), alongside the model name, version, license type, commercial-use decision, any thresholds, and the acceptable-use policy link, with the date you reviewed it. Recording it there makes the determination auditable, lets you re-check when a license changes between versions, and gives legal and procurement a single place to see which models are approved for commercial use and under what conditions.
Is this guide legal advice?
No. This is a review checklist to help you gather the right facts and spot the common gotchas — license type, commercial-use permission, thresholds, acceptable-use, redistribution, derivatives and output ownership. License terms vary, change between versions, and depend on your specific use and jurisdiction. Route anything ambiguous or material to a qualified lawyer; the checklist helps you ask the right questions, not answer them for you.