The SISAP 2024 Indexing Challenge invited replicable and competitive approximate similarity search solutions for datasets of up to 100 million real-valued vectors. Participants are evaluated on the search performance of their implementations under quality constraints. Using a subset of the deep features of a neural network model provided by the LAION-5B dataset, the challenge posed three tasks, each with its unique focus: The present paper describes the details of the challenge, the evaluation system that was developed with it, and gives an overview of the submitted solutions.