Chapter V · Section 2 · Obligations for providers of general-purpose AI models
Article 53 — Obligations for providers of general-purpose AI models
▼ Primary text, verbatim. Our annotations appear below, visibly separated.
1. Providers of general-purpose AI models shall:
(a) draw up and keep up-to-date the technical documentation of the model, including its training and testing process and the results of its evaluation, which shall contain, at a minimum, the information set out in Annex XI for the purpose of providing it, upon request, to the AI Office and the national competent authorities;
(b) draw up, keep up-to-date and make available information and documentation to providers of AI systems who intend to integrate the general-purpose AI model into their AI systems. Without prejudice to the need to observe and protect intellectual property rights and confidential business information or trade secrets in accordance with Union and national law, the information and documentation shall:
(i) enable providers of AI systems to have a good understanding of the capabilities and limitations of the general-purpose AI model and to comply with their obligations pursuant to this Regulation; and
(ii) contain, at a minimum, the elements set out in Annex XII;
(c) put in place a policy to comply with Union law on copyright and related rights, and in particular to identify and comply with, including through state-of-the-art technologies, a reservation of rights expressed pursuant to Article 4(3) of Directive (EU) 2019/790;
(d) draw up and make publicly available a sufficiently detailed summary about the content used for training of the general-purpose AI model, according to a template provided by the AI Office.
2. The obligations set out in paragraph 1, points (a) and (b), shall not apply to providers of AI models that are released under a free and open-source licence that allows for the access, usage, modification, and distribution of the model, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available. This exception shall not apply to general-purpose AI models with systemic risks.
3. Providers of general-purpose AI models shall cooperate as necessary with the Commission and the national competent authorities in the exercise of their competences and powers pursuant to this Regulation.
4. Providers of general-purpose AI models may rely on codes of practice within the meaning of Article 56 to demonstrate compliance with the obligations set out in paragraph 1 of this Article, until a harmonised standard is published. Compliance with European harmonised standards grants providers the presumption of conformity to the extent that those standards cover those obligations. Providers of general-purpose AI models who do not adhere to an approved code of practice or do not comply with a European harmonised standard shall demonstrate alternative adequate means of compliance for assessment by the Commission.
5. For the purpose of facilitating compliance with Annex XI, in particular points 2 (d) and (e) thereof, the Commission is empowered to adopt delegated acts in accordance with Article 97 to detail measurement and calculation methodologies with a view to allowing for comparable and verifiable documentation.
6. The Commission is empowered to adopt delegated acts in accordance with Article 97(2) to amend Annexes XI and XII in light of evolving technological developments.
7. Any information or documentation obtained pursuant to this Article, including trade secrets, shall be treated in accordance with the confidentiality obligations set out in Article 78.
This text is meant purely as a documentation tool and has no legal effect. The Union's institutions do not assume any liability for its contents. The authentic versions of the relevant acts, including their preambles, are those published in the Official Journal of the European Union and available in EUR-Lex.
Recital 101 — interpretive context
Providers of general-purpose AI models have a particular role and responsibility along the AI value chain, as the models they provide may form the basis for a range of downstream systems, often provided by downstream providers that necessitate a good understanding of the models and their capabilities, both to enable the integration of such models into their products, and to fulfil their obligations under this or…
Recital 104 — interpretive context
The providers of general-purpose AI models that are released under a free and open-source licence, and whose parameters, including the weights, the information on the model architecture, and the information on model usage, are made publicly available should be subject to exceptions as regards the transparency-related requirements imposed on general-purpose AI models, unless they can be considered to present a…
Recital 109 — interpretive context
Compliance with the obligations applicable to the providers of general-purpose AI models should be commensurate and proportionate to the type of model provider, excluding the need for compliance for persons who develop or use models for non-professional or scientific research purposes, who should nevertheless be encouraged to voluntarily comply with these requirements. Without prejudice to Union copyright law,…
What this means for you
In your terms · General-purpose AI provider duties
Model documentation and the downstream information pack describe training, evaluation and limitations at a level another engineering team can build on.
- Model documentation
- Downstream information pack
- Public training-content summary
Failure smells likeA downstream provider asks what they need in order to comply, and what you have to send is a model card written for a launch post.
In your terms · General-purpose AI provider duties
Fine-tuning someone else's model can make you a model provider with these duties for your modification.
- Provider-status assessment for fine-tunes
Obligations derived from this article
Scenarios that touch this provision
An open model, fine-tuned and sold inside your product
Illustrative Reading still settling
You took an open-weight model, fine-tuned it on your own data, and it now powers a paid feature in the product you sell.
- Your role
- Provider
- Where it lands
- Not classified In force 2 Aug 2025
- Decided by
- Chapter V, as the provider of the modified model, and separately whatever Article 6 says about the system you built on it.
What applies
What you have to be able to produce
- Downstream information pack
- Model documentation
- Onboarding notes for AI-touching roles
- Provider-status assessment for fine-tunes
- Public training-content summary
- Team enablement plan for people operating AI systems
- Written mandate for the model's authorised representative
What would change the answer
- The Article 53(2) exception covers models released under a free and open-source licence with public parameters, architecture and usage information, and it never covers a model with systemic risk.
- Recital 103 reads components provided against a price or otherwise monetised as outside the free and open-source exceptions. A recital is interpretive context, not operative law, and it is the weakest link in this row.
- Crossing the Article 51 systemic-risk threshold adds the Article 55 duties and removes the exception entirely.
An open-weight model on your own cluster, serving an internal copilot
Illustrative
You pulled open weights, you serve them on your own Kubernetes cluster, and an internal copilot calls them. Nothing leaves your network, and you control every log.
- Your role
- DeployerProvider
- Where it lands
- Not classified In force 2 Feb 2025
- Decided by
- The model is a general-purpose AI model, which the risk taxonomy does not classify at all. The copilot is the system, and it matches no Annex III use case.
What you have to be able to produce
- Disclosure pattern in the design system
- Onboarding notes for AI-touching roles
- Reusable disclosure component
- Team enablement plan for people operating AI systems
What would change the answer
- Fine-tune the weights and you may become the provider of the modified model. The Commission’s indicative criterion is a modification using more than a third of the original training compute, which is guidance, not a threshold in the Regulation.
- Article 2(12) puts systems released under free and open-source licences outside the Regulation, but never when they are placed on the market as high-risk or under Article 5 or Article 50.
- Because you run the model, the logs are under your control, which is the fact that decides who answers Article 19 or Article 26(6) if the system ever becomes high-risk.
If you would rather not read the law
The basics page explains the Regulation's own categories in order: scope, role, tier, date. The engineering view groups the obligations by the platform capability they demand.