⚡ Super fast clustering for high-dimensional vectors on CPUs (x86, ARM) and GPUs — for Python and C++. Faster clustering of vector embeddings than FAISS
☆93Oct 13, 2026Updated 3 weeks ago
Alternatives and similar repositories for SuperKMeans
Users that are interested in SuperKMeans are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ⚡ PDX: A Library for Fast Vector Search and Indexing on CPUs (x86, ARM) — for Python and C++. Index millions of vectors in seconds. Searc…☆97Updated this week
- ⚡ [WIP] DuckIR: A DuckDB extension for Information Retrieval. Introduces a state-of-the-art IVF index for lightweight but fast (filtered)…☆15Updated this week
- Segmented Code Adjustment Quantization (SAQ)☆29Sep 22, 2025Updated last year
- The repo has been moved to https://github.com/VectorDB-NTU/RaBitQ-Library. [SIGMOD 2025] Practical and Asymptotically Optimal Quantizatio…☆72Mar 30, 2026Updated 7 months ago
- A low-latency, billion-scale, and updatable graph-based vector store on SSD.☆159Oct 17, 2026Updated 2 weeks ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- A new query hardness measure for graph-based ANN indexes. Build unbiased workloads with this hardness to see the actual performance of yo…☆22May 6, 2026Updated 6 months ago
- [ICML'26] LEMUR reduces multi-vector retrieval for late interaction models such as ColBERT into regular single-vector retrieval.☆33Oct 6, 2026Updated last month
- [SIGMOD2026] Reveal Hidden Pitfalls and Navigate Next Generation of Vector Similarity Search with Task-Centric Benchmarks☆27Dec 31, 2025Updated 10 months ago