Chapter V · Section 1 · Classification rules
Article 51 — Classification of general-purpose AI models as general-purpose AI models with systemic risk
▼ Primary text, verbatim. Our annotations appear below, visibly separated.
1. A general-purpose AI model shall be classified as a general-purpose AI model with systemic risk if it meets any of the following conditions:
(a) it has high impact capabilities evaluated on the basis of appropriate technical tools and methodologies, including indicators and benchmarks;
(b) based on a decision of the Commission, *ex officio* or following a qualified alert from the scientific panel, it has capabilities or an impact equivalent to those set out in point (a) having regard to the criteria set out in Annex XIII.
2. A general-purpose AI model shall be presumed to have high impact capabilities pursuant to paragraph 1, point (a), when the cumulative amount of computation used for its training measured in floating point operations is greater than 10²⁵.
3. The Commission shall adopt delegated acts in accordance with Article 97 to amend the thresholds listed in paragraphs 1 and 2 of this Article, as well as to supplement benchmarks and indicators in light of evolving technological developments, such as algorithmic improvements or increased hardware efficiency, when necessary, for these thresholds to reflect the state of the art.
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 110 — interpretive context
General-purpose AI models could pose systemic risks which include, but are not limited to, any actual or reasonably foreseeable negative effects in relation to major accidents, disruptions of critical sectors and serious consequences to public health and safety; any actual or reasonably foreseeable negative effects on democratic processes, public and economic security; the dissemination of illegal, false, or…
Recital 111 — interpretive context
It is appropriate to establish a methodology for the classification of general-purpose AI models as general-purpose AI model with systemic risks. Since systemic risks result from particularly high capabilities, a general-purpose AI model should be considered to present systemic risks if it has high-impact capabilities, evaluated on the basis of appropriate technical tools and methodologies, or significant impact on…
Recital 112 — interpretive context
It is also necessary to clarify a procedure for the classification of a general-purpose AI model with systemic risks. A general-purpose AI model that meets the applicable threshold for high-impact capabilities should be presumed to be a general-purpose AI models with systemic risk. The provider should notify the AI Office at the latest two weeks after the requirements are met or it becomes known that a…
What this means for you
In your terms · Systemic-risk model obligations
Adversarial testing of the model is conducted and documented; the runs and their records are engineering work.
- Documented adversarial test runs for the model
In your terms · Systemic-risk model obligations
Evaluations, incident tracking and model-weight security are operational programs with schedules and evidence, not one-off exercises.
- Evaluation program with adversarial testing
- Model-weight security controls
Failure smells likeThe evaluation that would have found the capability was a benchmark run once, and nothing adversarial has been pointed at the model since.
In your terms · Systemic-risk model obligations
If your training compute approaches the presumption threshold, the notification and obligations clock starts with the training run, not the launch.
- Training-compute accounting
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.
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.