Commission Guidelines on the scope of the obligations for providers of general-purpose AI models under the AI Act
Guidance, not a law: the European Commission's reading of AI Act, Article 53 (obligations for providers of general-purpose AI models). It binds nobody by itself; the law it reads does.
Guidance on an AI governance rule, addressed to public and private bodies.
- Private right of action
- No
- Instrument type
- guidance published by a regulator
- Obligation class
- Disclosure, Governance, TDM
As of .
What the regulator expects
- A model is indicated to be a general-purpose AI model when its training compute is greater than 10^23 FLOP and it can generate language (text or audio), text-to-image, or text-to-video; a model that meets that criterion but, exceptionally, lacks significant generality or cannot competently perform a wide range of distinct tasks is not one, and a model that does not meet it but displays both is one (Section 2.1, paragraphs 17 and 20).
- Treat a general-purpose AI model as the same model through its whole lifecycle, which begins at the start of the large pre-training run, so that the documentation, the copyright policy and the training-content summary cover each model placed on the market and the systemic risk assessment and mitigation run continuously (Section 2.2, paragraphs 22 and 23).
- The provider is the actor that develops a general-purpose AI model, or has it developed on its behalf, and places it on the market, and an upstream actor that makes the model available to a downstream actor on the Union market is its provider (Section 3.1, paragraphs 49 and 55).
- A model is placed on the market when it is first made available on the Union market, for example through a software library, an API, a public repository, a physical copy, a cloud computing service, a copy on a customer infrastructure, a chatbot web interface or an app store, when a provider integrates its own model into its own AI system that is made available on the market, or when it is used for internal processes essential to a product or service for third parties or affecting the rights of natural persons in the Union (Sections 3.1.2 and 3.1.3, paragraphs 51 and 54).
- Where an upstream actor makes a model available outside the Union market and a downstream actor integrates it into an AI system placed on the Union market or put into service in the Union, the model is placed on the Union market at that point and the upstream actor is its provider, unless the upstream actor clearly and unequivocally excluded its distribution and use on the Union market, in which case the integrating downstream actor is the provider (Section 3.1.3, paragraph 56).
- A downstream modifier becomes the provider of the modified model only if the modification leads to a significant change in its generality, capabilities or systemic risk, indicated by training compute for the modification greater than a third of the original model training compute or, where that value cannot be known or estimated, a third of 10^25 FLOP for an original model with systemic risk and otherwise a third of 10^23 FLOP (Section 3.2, paragraphs 59 to 61).
- A modifier that becomes a provider limits its documentation to the modification and its copyright policy and training summary to the data used in the modification, and must also comply with Article 54; if the original model has systemic risk, the modified model is presumed to have high-impact capabilities and its provider must comply with the systemic risk obligations and notify the Commission (Sections 3.2.1 and 3.2.2, paragraphs 65 to 68).NIST AI RMFGOVERN 1.1
- A model is classified as a general-purpose AI model with systemic risk from the moment it meets a condition of Article 51(1), and the provider must notify the Commission without delay and in any event within two weeks after the presumption threshold is met or it becomes known that it will be met, which may be before training is complete, reporting the estimated compute in FLOP with two significant figures and the approach used to estimate it (Sections 2.3.1 and 2.3.2, paragraphs 26 to 31).NIST AI RMFGOVERN 1.1
- A provider that argues, with its notification, that a model exceptionally presents no systemic risk must substantiate the arguments and bears the burden of evidence against the presumption; planned or implemented mitigations are not suitable grounds, and presenting arguments does not suspend the obligations of a provider of a model with systemic risk (Section 2.3.3, paragraphs 32, 33, 39 and 40).
- The exceptions in Article 53(2) and Article 54(6), covering Article 53(1), points (a) and (b), and Article 54, apply only to a model without systemic risk released under a licence that allows access, use, modification and distribution without payment or other monetization, with the parameters including the weights, the information on model architecture and the information on model usage made publicly available (Sections 4.1 and 4.2, paragraphs 70 to 89).
- A provider that meets the open-source conditions remains bound by the Article 53(1), point (c), duty to put in place a copyright policy, including identifying and complying with a reservation of rights under Article 4(3) of Directive (EU) 2019/790, and by the point (d) duty to produce a summary of the content used for training (Section 4.1, paragraph 72).NIST AI RMFMAP 4.1NIST AI RMFMAP 2.3
- A provider of a general-purpose AI model placed on the market before must take the necessary steps to comply by and is not required to retrain or unlearn the model where that is not possible, where information about the training data is unavailable or where retrieval would cause disproportionate burden, but must clearly disclose and justify each such instance in the copyright policy and the training-content summary (Section 5.3, paragraphs 106 and 108).NIST AI RMFMAP 4.1NIST AI RMFMAP 2.3
- The AI Office takes a collaborative, staged and proportionate approach: for a provider that adheres to a code of practice assessed as adequate, enforcement focuses on monitoring that adherence; a provider that does not adhere is expected to demonstrate compliance by other adequate means and may face more requests for information and for access to evaluate its model; and the Commission will enforce with fines from against providers not fully compliant on that date (Sections 5.1 to 5.3, paragraphs 91, 92, 99 and 112).
- The AI Office reads the Article 55(1), point (c), duty to report serious incidents as covering serious cybersecurity breaches related to the model or its physical infrastructure, including exfiltration of model parameters and cyberattacks, and treats as a serious incident any incident or malfunctioning of a general-purpose AI model that directly or indirectly leads to an event listed in Article 3(49), points (a) to (d) (Section 5.2, paragraph 100).
In the frameworks
- NIST AI RMF
- GOVERN 1.1Legal and regulatory requirements involving AI are understood, managed, and documented.
- MAP 2.3Scientific integrity and TEVV considerations are identified and documented, including those related to experimental design, data collection and selection (e.g., availability, representativeness, suitability), system trustworthiness, and construct validation.
- MAP 4.1Approaches for mapping AI technology and legal risks of its components – including the use of third-party data or software – are in place, followed, and documented, as are risks of infringement of a third party’s intellectual property or other rights.
- NIST AI 600-1
- GAI-RISK-07Human-AI Configuration
- GAI-RISK-10Intellectual Property
- GAI-RISK-12Value Chain and Component Integration
- NIST AI 200-2 Draft
- OWASP LLM Top 10
- LLM03:2026Excessive Agency
- OWASP Agentic Top 10
- ASI09Human-Agent Trust Exploitation
- MIT mitigations Draft
- FINOS AIGF
- AIR-PREV-005System Acceptance Testing
- AIR-PREV-006Data Quality & Classification/Sensitivity
- AIR-PREV-007Legal and Contractual Frameworks for AI Systems
- AIR-PREV-024Human-in-the-Loop Action Approval Gate
- AIR-DET-004AI System Observability
- AIR-DET-011Human Feedback Loop for AI Systems
1 more
- AIR-DET-021Agent Decision Audit and Explainability
- ETSI EN 304 223
- 5.1.4-1Capability for human oversight designed in and maintained.
- 5.2.1-1Full inventory of assets, including their dependencies and connections.
- 5.2.4-1Developers keep an audit trail of system design and post-deployment maintenance plans and offer it downstream.
- 5.2.4-2.1Minimum record for training data: its source, such as a page URL, and when it was collected.
- 5.4.2-1Operators log system and user actions.
Our reading of where this law's duties sit in each framework, and in the NIST AI RMF, line by line beside each duty above. It never says that running a control meets the law. How we read a framework against the law
Identifiers refer to ETSI EN 304 223 V2.1.1 (2025-12), © ETSI 2025, all rights reserved. ETSI owns the standard; no ETSI text (titles or sentences) is reproduced here. The standard is free to download from ETSI.
Who enforces it
Enforcement body
The Commission, acting through the AI Office, which supervises and enforces the obligations of providers of general-purpose AI models; the guidelines are its published reading of those obligations and carry no sanction of their own.
Settledness
The guidelines are the Commission's own reading, and paragraph 9 says that an authoritative interpretation of the AI Act may only be given by the Court of Justice of the European Union.
- As of
- Open questions
- When is the original provider, and when a downstream actor, the one that modifies a general-purpose AI model, given that the guidelines call for a case-by-case assessment in which control over the model weights may be an important factor?
What this law does
The guidelines are Communication from the Commission C(2025) 7719 final, dated . Communication to the Commission C(2025) 5045 final, dated , approved the content of the draft guidelines. The approval Communication says that the guidelines will be formally adopted by the Commission at a later date, when all language versions are available, and that it is only from that moment that they will be applicable.
Paragraph 7 says that Article 96(1) of the AI Act requires the Commission to develop guidelines on the practical implementation of the Act, and that these guidelines focus on the scope of the obligations for providers of general-purpose AI models. Paragraph 7 says that the guidelines solely concern the AI Act and are not applicable to other Union laws, including on liability.
Paragraph 9 says that the guidelines are not binding for providers of general-purpose AI models and that an authoritative interpretation of the AI Act may only be given by the Court of Justice of the European Union. Paragraph 9 also says that the guidelines set out the interpretation and application of the AI Act by the Commission, on which it will base its enforcement action.
Paragraph 9 adds that a case-by-case assessment will always be necessary to account for the specifics of each individual case. Article 101(1), point (a), of the AI Act grounds a fine on a provider of general-purpose AI models in its intentional or negligent infringement of the relevant provisions of the Regulation.
Paragraph 17 gives as an indicative criterion for a general-purpose AI model that its training compute is greater than 10^23 FLOP and that it can generate language (whether in the form of text or audio), text-to-image, or text-to-video.
Paragraph 20 says that a model that meets that criterion but, exceptionally, does not display significant generality or is not capable of competently performing a wide range of distinct tasks is not a general-purpose AI model, and that a model that does not meet the criterion but exceptionally displays both is one.
Paragraph 22 says that the Commission considers the lifecycle of a general-purpose AI model to begin at the start of the large pre-training run, and that later development by or on behalf of the provider, before or after the model is placed on the market, forms part of the same model lifecycle rather than giving rise to new models.
Paragraph 26 says that from the moment a general-purpose AI model meets either condition of Article 51(1), the model is classified as a general-purpose AI model with systemic risk and its provider must comply with the relevant obligations. Paragraph 29 says that the provider must notify the Commission without delay and in any event within two weeks after the requirement is met or it becomes known that it will be met.
Paragraph 30 says that a notification may be required before training is complete, if the provider can reasonably foresee that the requirement leading to the presumption of high-impact capabilities is reasonably likely to be met. Paragraph 33 says that the burden of adducing evidence that the presumption deriving from the quantitative thresholds should not apply is to be borne by the provider.
Paragraph 39 says that arguments that a model does not present systemic risks because of mitigations already or planned to be implemented are not suitable grounds for excluding it from classification as a general-purpose AI model with systemic risk. Paragraph 40 says that presenting arguments with the notification does not suspend the obligations of the provider of a general-purpose AI model with systemic risk.
Paragraph 43 says that the Commission may designate a model under Article 52(1) where the provider of a model meeting the condition in Article 51(1), point (a), failed to notify, and that the provider may be fined under Article 101. Paragraph 49 says that, if an actor develops a general-purpose AI model and places it on the market, that actor is the provider.
Paragraph 51 says that a general-purpose AI model made available for the first time on the Union market via an application programming interface should be considered to be placed on the market. Paragraph 51 also lists a model used for internal processes that are essential for providing a product or service to third parties or that affect the rights of natural persons in the Union.
Paragraph 54 says, quoting recital 97, that when the provider of a general-purpose AI model integrates an own model into its own AI system that is made available on the market or put into service, that model should be considered to be placed on the market.
Paragraph 56 says that, where an upstream actor makes a model available to a downstream actor outside the Union market, the model should be considered to be placed on the Union market once the system into which it is integrated is placed on the Union market or put into service in the Union.
Paragraph 56 also says that the upstream actor should then be considered the provider of the model, unless it has excluded in a clear and unequivocal way the distribution and use of the model on the Union market. Paragraph 59 says that the Commission considers a downstream modifier to become the provider of the modified general-purpose AI model only if the modification leads to a significant change in the generality, capabilities, or systemic risk of the model.
Paragraph 60 gives as an indicative criterion that the training compute used for the modification is greater than a third of the training compute of the original model. Paragraph 61 says that, where the modifier cannot be expected to know or estimate that value, the threshold becomes a third of 10^25 FLOP for an original model with systemic risk and otherwise a third of 10^23 FLOP.
Paragraph 65 says that the documentation required by Article 53(1), points (a) and (b), is limited to information on the modification, while the copyright policy and the summary of the content used for training are limited to the data used as part of the modification. Paragraph 67 says that, if a downstream actor modifies a general-purpose AI model with systemic risk so that it becomes the provider of the modified model, the resulting model is presumed to have high-impact capabilities.
Paragraph 70 says that, for providers meeting the conditions referred to in Section 4.2, the obligations it lists do not apply unless their model is a general-purpose AI model with systemic risk. Paragraph 70 lists the obligation in Article 53(1), point (a), to draw up and keep up to date the technical documentation of the model.
Paragraph 70 lists the obligation in Article 53(1), point (b), to draw up, keep up to date and make available information and documentation to providers of AI systems who intend to integrate the model. Paragraph 70 also lists Article 54, the obligation to appoint an authorised representative for providers of general-purpose AI models established in third countries.
Paragraph 72 says that providers meeting those conditions are not exempted from the obligation in Article 53(1), point (c), to put in place a policy to comply with Union copyright law. Paragraph 72 adds that, for the same reasons, they are not exempted from the obligation in Article 53(1), point (d), to produce a summary about the content used for training.
Paragraph 75 says that, if one of the rights to access, use, modify and redistribute is missing, the licence cannot be considered free and open-source under the AI Act. Paragraph 80 gives as an example of a restriction that disqualifies a licence a usage restriction triggered by user scale thresholds, such as requiring additional licensing if monthly active users exceed a certain number.
Paragraph 83 lists as a form of monetization a model provided under a dual licensing model that allows free academic use but requires payment for commercial usage or use over a certain scale.
Paragraph 84 says that access, use, modification, or redistribution of the model requiring the collection or other processing of personal data should be treated in the same manner as monetization strategies, unless that processing is exclusively and strictly limited to the security of the model and without any commercial or financial gain.
Paragraph 91 says that providers of general-purpose AI models can demonstrate compliance with the obligations in Articles 53(1) and 55(1) by adhering to a code of practice that is assessed as adequate by the AI Office and the Board. Paragraph 91 also says that, for providers that adhere to such a code, the Commission will focus its enforcement activities on monitoring their adherence to the code of practice.
Paragraph 92 says that providers that do not adhere to such a code may be subject to a larger number of requests for information and requests for access to conduct model evaluations throughout the entire model lifecycle. Paragraph 99 says that the AI Office will take a collaborative, staged, and proportionate approach.
Paragraph 100 says that the AI Office considers the obligation to report serious incidents under Article 55(1), point (c), to cover serious cybersecurity breaches related to the model or its physical infrastructure, including the exfiltration of model parameters and cyberattacks.
Paragraph 100 also says that the AI Office considers a serious incident in the context of Chapter V as any incident or malfunctioning of a general-purpose AI model that directly or indirectly leads to any of the events listed in Article 3(49), points (a) to (d), for AI systems. Paragraph 103 says that the powers of the Commission include imposing fines of up to 3% of global annual turnover or EUR 15 million, whichever is higher, starting on .
Article 111(3) of the AI Act requires providers of general-purpose AI models that have been placed on the market before to take the necessary steps in order to comply with the obligations laid down in the Regulation by .
Paragraph 108 says that providers of general-purpose AI models placed on the market before are not required to conduct retraining or unlearning where that is not possible for past actions, where some information about the training data is not available, or where its retrieval would cause the provider disproportionate burden. Paragraph 108 adds that such instances must be clearly disclosed and justified in the copyright policy and in the summary of the content used for training.
Paragraph 112 says that the lack of enforcement in the first year from does not put into question the applicability of the obligations laid down in Chapter V from onwards. Paragraph 112 also says that, from onwards, the Commission will enforce with fines compliance with all obligations by providers of general-purpose AI models who are not fully compliant on that date.
The Commission page on the General-Purpose AI Code of Practice says that its Transparency and Copyright chapters offer all providers of general-purpose AI models a way to demonstrate compliance with their obligations under Article 53 of the AI Act. The same page describes the Code of Practice as a voluntary tool, prepared by independent experts in a multi-stakeholder process, designed to help industry comply with the obligations of the AI Act for providers of general-purpose AI models.