General-purpose AI model reach as criterion for systemic risk : collection of external scientific studies on general-purpose AI models under the EU AI Act

Under the EU AI Act, systemic risks of general-purpose AI (GPAI) models are assumed to increase with model "reach". This report proposes a method for operationalising, and measuring "reach" so that it may be used, where appropriate, as one criterion amongst others for determining whether a GPAI model should be classified as a GPAI model with systemic risk. This report considers specific systemic risks created by model reach, such as risks from model biases, i.e. systemic risk which become relevant when models are widely used, regardless of whether their capabilities are at the technological frontier. In this report, reach is defined as the number of people who directly interact with a given GPAI model. Potential metrics for measuring reach are identified, including access via user interfaces and APIs. A concrete proposal for the design of a reach trigger is presented, which includes overall reporting thresholds for model providers, reach metrics to be reported, and calibration of the reach trigger. The proposal aims to balance comprehensive coverage with minimal reporting burden, and to provide a framework for incorporating reach considerations in the determination of whether a GPAI model presents systemic risks, in complement to other considerations related to capabilities, safety benchmarks and compute discussed in other reports of this collection.