What AI says about ANN Benchmarks
Data as of Oct 20, 2026Based on 9,648 AI responses
Reviewed by Dimitry Apollonsky
AI summary
ANN-Benchmarks is a benchmark platform for evaluating approximate nearest neighbor search algorithms across various datasets and distance metrics.
Mentioned in
<1%
across ANN Benchmarks’s markets · since Jul 5
Where AI mentions ANN Benchmarks
Position in answers
- Named first0%
- 2nd or 3rd29%
- Later71%
Each engine’s share of its own answers across ANN Benchmarks’s markets · since Jul 5
- ChatGPT Search<1%
- Google AI Mode<1%
A cited page to review
This page is cited in 1% of the answers that name ANN Benchmarks.
Review this page on your site for accurate product details and clear explanations of who it helps.
All-time evidence through 2026-09-25.
Review the page on ann-benchmarks.com (opens in a new tab)
Questions and answers
Sources AI cites
ann-benchmarks.com 8%Other sites 92%
- 20%
- [2505.17810] VIBE: Vector Index Benchmark for Embeddings · 12% (opens in a new tab)
- [1807.05614] ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms · 4% (opens in a new tab)
- [2603.10765] RAGPerf: An End-to-End Benchmarking Framework for Retrieval-Augmented Generation Systems · 4% (opens in a new tab)
- 16%
- Optimizing RAG: A Guide to Choosing the Right Vector Database | by Mutahar Ali | Medium · 4% (opens in a new tab)
- Optimizing RAG: A Guide to Choosing the Right Vector Database | by Mutahar Ali | Medium · 4% (opens in a new tab)
- Benchmarking Vector Databases: What I Learned from Pushing 500K Vectors Through Their Limits | by Alex Chen | Everyday AI | Medium · 4% (opens in a new tab)
- Evaluating Vector Databases 101 - Medium · 4% (opens in a new tab)
