Direct answer

When are you a provider of a GPAI model under the AI Act?

6 obligations under the AI Act bear on this, of which 6 apply today.

First step: Record per requirement which standard or specification you rely on, and justify every departure.

Whether you are a provider of a GPAI model is not a matter of what you call yourself but of what you do with the system. Across the 6 obligations there are 18 conditions and exceptions that decide it. Below they are listed per provision, with the official source. Likely role: provider of a gpai model.

The conclusion and your first steps

Preliminary reading · Articles 40 to 42: standards, common specifications and presumption of conformity

What is open is the anchoring of the duty holder. Of the three Articles only Article 41(5) contains a rule of conduct addressed to a role this graph knows: providers of high-risk AI systems or general-purpose AI models must duly justify that they have adopted at least equivalent technical solutions where they do not apply a common specification. The object is anchored on that paragraph. A defensible alternative reading treats Articles 40 to 42 as entirely institutional, with an empty duty holder and `out_of_scope`, and hangs the justification on Article 11 and Annex IV, where the technical documentation is described. On that reading the recommended action and the file below move to the object on Article 11; the substance does not change, the basis does. Also open is where the justification must be recorded. Article 41(5) prescribes no form, no place and no recipient. We read it as belonging in the technical documentation, because that is the only file a market surveillance authority can request under Article 21; that is an inference and not text. Not open is the dating: Articles 40, 41 and 42 sit in Chapter III, Section 5, and that Section is not excepted in the third paragraph of Article 113, so the general application date of the second paragraph governs, 2 August 2026.

The text of the provision is settled. How it plays out has not been decided in case law or guidance, so this is our reasoned reading and not established law. Weigh it yourself, or put it to your own lawyer.

Preliminary reading · Article 4a: legal basis for bias testing with special categories of personal data

Two things are open here, and the risk runs the other way round than with a right such as Article 86: a broad reading here benefits the controller and not the data subject, because this concerns data on ethnicity, health, religion, trade union membership and sexual orientation. Where in doubt the narrow reading is therefore the safe one. First, the reach of "other AI systems and models" in paragraph 2, which on its face covers any AI system and any model and for which no delimitation exists. We read it on its face, but with the threshold in paragraph 2, point (a), as the real boundary: without a consequence for health and safety, fundamental rights or prohibited discrimination there is no basis. A defensible alternative reading is that paragraph 2 is confined to systems comparable to the examples in recital 9, such as scoring tools for permits and public services. Second, the relationship with Article 9 GDPR. Recital 9 states that the extension is subject to the same limitations, conditions and safeguards and thereby ensures compliance with Article 9(2), point (g), of Regulation (EU) 2016/679, so we read Article 4a as the Union law measure that point requires, with the safeguards carried by the six conditions themselves. The counterargument stands against that and has not gone away, but it has narrowed since 27 July 2026: the anchoring sits in a recital and not in the article, and the article itself designates no ground from Article 9(2). What no longer supports that counterargument is Article 2(7). Until 27 July 2026 that paragraph left the GDPR unaffected without reservation, but it was replaced by Article 1, point 2(b), of Regulation (EU) 2026/1744 and now reads: "Union law on the protection of personal data, privacy and the confidentiality of communications applies to personal data processed in connection with the rights and obligations laid down in this Regulation. Without prejudice to Articles 4a and 59 of this Regulation, this Regulation shall not affect Regulation (EU) 2016/679 or (EU) 2018/1725, or Directive 2002/58/EC or (EU) 2016/680." The Union legislature therefore carved the reservation out for Article 4a precisely, which points towards reading Article 4a as the Union law measure itself rather than a mere cross-reference to the GDPR. Anyone citing this object while quoting the former wording of Article 2(7) is quoting a replaced provision. A defensible alternative reading remains that a national or Union measure with specific safeguards is still needed alongside it, but it now rests only on the absence of an express designation in the article itself. On the date from which the basis operates, part is settled and part is not. What is settled is what recital 9 says, namely that the basis should apply from the date of entry into application of Regulation (EU) 2024/1689; that has been read and is not a house reading. What remains open is which date this object therefore carries. We hold to 27 July 2026, the day Article 4a entered the text, because a basis that was not yet there was in fact not available. The alternative reading follows recital 9 literally and lets the basis reach back to the date of application of the base Regulation. That difference is not academic for anyone who has to justify processing from that period. The editorial statement below marks that choice as our inference.

This applies now

Articles 40 to 42: standards, common specifications and presumption of conformityApplicable
Article 4a: legal basis for bias testing with special categories of personal dataApplicable
Article 52: notification of a GPAI model with systemic riskApplicable
Article 53: GPAI model providersApplicable
Article 54: authorised representative of a provider of a GPAI modelApplicable
Article 55: GPAI models with systemic riskApplicable

What decides whether this is about you

Articles 40 to 42: standards, common specifications and presumption of conformity

Applies when: The presumption in Article 40(1) arises only where the references of the harmonised standard have been published in the Official Journal of the European Union in accordance with Regulation (EU) No 1025/2012, and it reaches only to the extent that those standards cover those requirements or obligations. The same holds for the cybersecurity certification of Article 42(2), the references of which must likewise have been published in the Official Journal.
Applies when: The justification duty of Article 41(5) arises only where a common specification has actually been established by implementing act for the requirement concerned and the provider does not apply it. Where no such specification exists, there is nothing to depart from and you demonstrate conformity by the ordinary route.

Unless: A presumption of conformity is not a finding of compliance. The text says the system shall be presumed to be in conformity, and only in so far as the standard or the specification covers the requirements or obligations concerned. Outside that coverage the burden of proof rests fully on the provider, and a market surveillance authority can rebut the presumption where the system in fact does not meet the requirements.
Unless: Article 41(4) makes a common specification lapse as soon as the standard exists: when reference to a harmonised standard is published in the Official Journal of the European Union, the Commission repeals the implementing acts, or parts thereof, which cover the same requirements or obligations. A file leaning on a repealed specification thereby loses its basis.

Article 4a: legal basis for bias testing with special categories of personal data

Applies when: Paragraph 1 is open only to the provider of a high-risk AI system, and only to the extent that the processing is strictly necessary to detect and correct bias in accordance with Article 10(2), points (f) and (g). The deployer cannot rely on this paragraph, not even for a high-risk system; for the deployer the route runs through paragraph 2.
Applies when: Paragraph 2 is open to providers and deployers of other AI systems and models and to deployers of high-risk AI systems, but carries its own substantive threshold: the processing must be strictly necessary in view of possible biases that are likely to affect the health and safety of persons, have a negative impact on fundamental rights or lead to discrimination prohibited under Union law, especially where data outputs influence inputs for future operations. Bias without one of those consequences falls outside it.
Applies when: The six conditions in paragraph 1 are cumulative and, through paragraph 2, point (b), apply to the wider circle as well: (a) other data, including synthetic or anonymised data, demonstrably do not suffice; (b) technical limitations on re-use apply plus state of the art security and privacy preserving measures, including pseudonymisation; (c) there is strict access control with documentation and confidentiality; (d) the data are not transmitted, transferred or otherwise accessed by other parties; (e) they are deleted once the bias has been corrected or the retention period ends, whichever comes first; (f) the record of processing activities states why the processing was strictly necessary and why the objective could not be achieved with other data.

Unless: Paragraph 2 closes by providing that it creates no obligation to carry out bias detection and correction. Article 4a is therefore a basis and not an instruction: without carrying out such processing there is nothing to comply with under this article, there is no date by which anything must be done, and outside the purpose of bias detection and correction it grants no room at all.

Article 52: notification of a GPAI model with systemic risk

Applies when: Applies to the provider of a general-purpose AI model as soon as that model meets the condition in Article 51(1), point (a): high impact capabilities, which under Article 51(2) are presumed where the cumulative amount of computation used for its training, measured in floating point operations, is greater than 10^25. The two-week period runs from the moment that requirement is met or it becomes known that it will be met. The second route to systemic risk, a Commission designation under Article 51(1), point (b), or Article 52(4), is not covered here: Article 52(1) refers only to point (a).

Unless: For general-purpose AI models placed on the market before 2 August 2025, Article 111(3) provides that the provider shall take the necessary steps to comply with the obligations of this Regulation by 2 August 2027. For those models the governing date is therefore 2 August 2027 and not the two-week period.

Article 53: GPAI model providers

Applies when: The party is a provider of a GPAI model placed on the Union market.
Applies when: For models placed on the market from 2 August 2025, the duties apply from that time. Models placed on the market before 2 August 2025 must comply by 2 August 2027.

Unless: The open-source exception is limited and retains, among other things, the copyright policy and public training-content summary. Additional duties apply to models with systemic risk.

Article 54: authorised representative of a provider of a GPAI model

Applies when: Applies where the model qualifies as a general-purpose AI model within the meaning of Article 3(63), its provider is established in a third country, and that model is placed on the Union market. The appointment is made by written mandate within the meaning of Article 3(5), which is not only given but also accepted, and it is made before the model is placed on the market. The moment at which the latter occurs is fixed less sharply for a model than for a system; see the editorial interpretation.
Applies when: For models placed on the market from 2 August 2025, the appointment duty applies from that moment. Providers of models placed on the market before 2 August 2025 shall, under Article 111(3), take the necessary steps to comply with the obligations of the Regulation by 2 August 2027.

Unless: Paragraph 6 excludes the obligation for providers of AI models released under a free and open-source licence that allows access, usage, modification and distribution, and whose parameters, including the weights, the information on the model architecture and the information on model usage, are made publicly available. That exception falls away as soon as the model presents a systemic risk. Whether a given release qualifies is a factual test that has not been settled anywhere; we read it narrowly, so a partially public release does not qualify.

Article 55: GPAI models with systemic risk

Applies when: The GPAI model has high-impact capabilities, presumed above 10^25 FLOPs of cumulative training compute, or is designated by the Commission.

Unless: The GPAI Code of Practice can, following the adequacy assessment, serve as a means to demonstrate compliance.

These are the questions you answer yourself. Praxikon shows which condition sits in which provision; whether your system meets it is yours to establish.

Heavy fine-tuning makes you the model provider
A European scale-up fine-tunes an existing general-purpose AI model for its own product, using more compute than one third of the compute used to train the original model.
Provenance: The Commission guidelines on the scope of the GPAI obligations address this case when determining when someone becomes a model provider themselves. The document is non-binding.
Estimate your fine-tuning compute against the original model before you start, because exceeding one third of it makes you the provider, with documentation, copyright and training-content duties limited to your modification.
Commission Guidelines C(2025) 5045 final, 18.7.2025, scope of the obligations for GPAI model providers
financial services
Light fine-tuning does not make you a model provider
A bank fine-tunes an existing general-purpose AI model on its own product documentation and customer questions, using a fraction of the original compute, and builds a customer chatbot around it that it offers under its own name.
Provenance: The Commission guidelines on the scope of the GPAI obligations address this case when determining when someone becomes a model provider themselves. The document is non-binding.
If your fine-tuning stays well below one third of the original compute you do not become the model provider, but the obligations for the AI system you offer under your own name still apply.
Commission Guidelines C(2025) 5045 final, 18.7.2025, scope of the obligations for GPAI model providers
Modifying a systemic-risk model pulls the heaviest duties to you
A downstream actor modifies an existing systemic-risk model so substantially that the change exceeds the threshold, and publishes the result as its own model.
Provenance: The Commission guidelines on the scope of the GPAI obligations address this case when determining when someone becomes a model provider themselves. The document is non-binding.
Where a modification of a systemic-risk model crosses the threshold, the result is presumed to have high-impact capabilities, so estimate the compute in advance and notify the Commission within two weeks.
Commission Guidelines C(2025) 5045 final, 18.7.2025, scope of the obligations for GPAI model providers
technology and software
Open source in name, but not within the meaning of the Regulation
Three providers call their model open source. The first licence allows non-commercial research only. The second requires a separate commercial licence once monthly active users pass a threshold. The third gives the model away for free but hosts it exclusively on its own platform where visitors are served paid advertisements.
Provenance: The Commission guidelines on the scope of the GPAI obligations address this case when determining when someone becomes a model provider themselves. The document is non-binding.
A usage restriction is not automatically fatal: you may include specific, proportionate and non-discriminatory safety terms, whereas a monthly active user threshold or a separate commercial licence disqualifies the licence.
Commission Guidelines C(2025) 5045 final, 18.7.2025, scope of the obligations for GPAI model providers

When a downstream party that fine-tunes becomes a GPAI provider itself
The Commission guidelines of 18 July 2025 (C(2025) 5045 final) on the scope of the obligations for providers of general-purpose AI models state in point (61) that it is not necessary for every modification of such a model to lead to the downstream modifier being considered the provider of the modified model, in line with the Blue Guide, which states that a product subject to important changes or overhauls aiming to modify its original performance, purpose or type may be considered a new product. Point (62) states that the Commission considers a downstream modifier to become the provider of the modified model only if the modification leads to a significant change in the model's generality, capabilities or systemic risk. Point (63) sets the indicative criterion: a downstream modifier is considered to be the provider where the training compute used for the modification is greater than a third of the training compute of the original model. Point (64) states that where the downstream modifier cannot be expected to know that value, for example because it has not been communicated by the provider of the original model, and cannot estimate it, the threshold is replaced by a third of 10 to the power of 25 FLOP where the original model is a model with systemic risk, and otherwise by a third of 10 to the power of 23 FLOP. Point (65) explains that a modification of that size is expected to display a significant change justifying the transparency obligations of Article 53(1)(a) and (b), that such a modification can be expected to have used a significant amount of data relevant to the copyright policy and the public summary of training content under Article 53(1)(c) and (d), and that where the original model has systemic risk the modified model can be expected to present significantly different systemic risk. Point (67) notes that currently few modifications meet this criterion, that the number of downstream modifiers becoming providers may increase over time, and that the criterion is thus primarily forward-looking. Point (68) states that in the case of a modification the obligations are limited to that modification: the documentation under Article 53(1)(a) and (b) is limited to information on the modification, and the copyright policy under point (c) and the summary of training content under point (d) are limited to the data used as part of the modification. Point (69) states that a downstream modifier who becomes a provider must also comply with Article 54, which means appointing an authorised representative established in the Union to the extent that the modifier is itself established outside the Union. Point (70) states that where a downstream actor modifies a model classified as having systemic risk in such a way that they become the provider of the modified model, the resulting model is presumed to have high-impact capabilities and is therefore considered a model with systemic risk, and point (71) states that the modifier must then comply with the obligations for providers of models with systemic risk and notify the Commission in line with Article 52(1).
Commission Guidelines C(2025) 5045 final, 18.7.2025, Section 3.2 points (60) to (67) and Sections 3.2.1 and 3.2.2, points (68) to (71)

Read the official sourceChecked on 8 August 2026

General interpretation, not legal advice. Checked against Regulation (EU) 2024/1689 and the Digital Omnibus (EU) 2026/1744; the official source remains authoritative.

Full map for your situation

When are you a provider of a GPAI model under the AI Act?

This applies now

What decides whether this is about you

Follow-up questions

Source and locator

Implement the GPAI provider obligations for each model

Zahed Ashkara

When are you a provider of a GPAI model under the AI Act?

This applies now

What decides whether this is about you

How this looks in practice4 practice examples

What the Commission says1 guidance statement

Follow-up questions

Source and locator

Implement the GPAI provider obligations for each model

Zahed Ashkara