The Excellence
Directory Platform Template

Billion-scale benchmark dataset containing 96-dimensional deep learning image embeddings. Provides real-world proxy for testing distributed systems and GPU-accelerated vector search at scale.

Billion-scale benchmark dataset containing 128-dimensional SIFT descriptors of one billion images. Widely used standard for evaluating approximate nearest neighbor search algorithms at scale.

BEIR (Benchmarking IR) is a benchmark suite for evaluating information retrieval and vector search systems across multiple tasks and datasets. Useful for comparing vector database performance.

A collection of datasets curated by Intel Labs specifically for evaluating and benchmarking vector search algorithms and databases.