---
title: "Open model licenses: what "open" actually means"
description: "Open-weight is not open-source. A guide to the licenses behind the leading open AI models and what they actually permit in a business context."
date: 2026-03-15
tags: [Licenses, Open models]
url: "https://ai.malagoli.me/en/blog/licenze-modelli-open-cosa-significa"
locale: en_US
---

# Open model licenses: what "open" actually means

<!-- 2026-03-15 · Licenses · Open models -->

The word "open" gets used very loosely in the AI world. The licenses behind the models, however, differ significantly — and reading them before adoption is not optional.

***

In AI marketing, "open" has become an almost empty word: it gets applied to models with very different licenses, some permissive, others with precise commercial restrictions. Before building a product or service on an "open" model, it's worth reading what that actually means in that specific case.

## Open-weight is not open-source

Most models called "open" release the trained weights, not the training code or the data used to train them. The technically correct term is open-weight: you can run the model, partially inspect it, and adapt it, but you cannot reproduce its training from scratch. It's a distinction that matters most when you need to demonstrate, in an audit, exactly how a system was built.

## The main licenses and what they permit

- Apache 2.0 or MIT (used by several Qwen and Mistral models): among the most permissive, free commercial use, few restrictions.
- Llama Community License: permits commercial use but with specific conditions — for example, thresholds tied to monthly active users beyond which a separate license from Meta is required.
- Gemma license: commercial use permitted but with acceptable-use clauses that must be respected.
- Research-only licenses: some models, especially newer or experimental versions, are released for research use only, not commercial use.

## Why it matters for a business, not just for a lawyer

The risk isn't theoretical: a license that prohibits or limits commercial use, if ignored, exposes the company to a contractual breach that may only be discovered years later, once the system is already part of core processes. You should also check redistribution rights (can you embed the model in a product you sell?) and rights over a fine-tuned model (who owns the weights resulting from your own fine-tuning?).

## The checklist we apply before adopting a model

- Is commercial use explicitly permitted under the current license, not an earlier version of the model?
- Are there thresholds (users, revenue, volume) beyond which the license changes?
- Is fine-tuning permitted, and who holds the rights to the resulting weights?
- Is redistribution permitted within a product or service offered to third parties?

None of these checks slow a project down if done at the start. They do slow it down — and cost far more — if skipped and discovered later.

***

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