When is a GPAI model classified as having systemic risk?
Article 51 classifies a general-purpose AI model as a GPAI model with systemic risk if it has high-impact capabilities, or if the Commission designates it after an ex officio assessment or a qualified alert from the scientific panel using Annex XIII criteria.
The Act creates a compute-based presumption: a GPAI model is presumed to have high-impact capabilities when the cumulative computation used for training is greater than 10^25 floating point operations. Article 52 then requires notification to 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.
- Record the model's training compute estimate, methodology, and supporting evidence before market placement decisions.
- Escalate if training compute exceeds 10^25 FLOP or if model reach, modalities, autonomy, scalability, tools, user base, or training data suggest Annex XIII significance.
- If relying on the Article 52 exception argument, keep objective evidence for why the model does not present systemic risk despite meeting the high-impact presumption.
- Track Commission designation and reassessment decisions because systemic-risk status changes the provider duty set.
Primary legal text for Article 51 classification, Article 52 notification and reassessment, and Annex XIII designation criteria.
Commission guidance explaining GPAI scope, the systemic-risk presumption, notification to the AI Office, and training-compute estimation context.