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KIOXIA Achieves 4.8 Billion High-Dimensional Vector Search Database on a Single Server, with 7.8x Index Build Time Acceleration via GPUs

Leveraging the NVIDIA cuVS Library with KIOXIA AiSAQ Technology to Index Vectors of 1024 Dimensions with Minimal DRAM Use

SAN JOSE, Calif.--(BUSINESS WIRE)--Kioxia America, Inc. today announced the successful demonstration of high-dimensional vector search scaling to 4.8 billion vectors on a single server using its open-source KIOXIA AiSAQ™ approximate nearest neighbor search (ANNS) technology. Additionally, Kioxia demonstrated a significant reduction in index build time by leveraging GPU acceleration through NVIDIA cuVS. These two achievements mark a significant advancement for retrieval augmented generation (RAG) search solutions. Continued development is underway to support larger-scale deployments beyond 4.8 billion vectors.

Scaling vector databases into the billions requires rethinking both memory and compute. By combining AiSAQ SSD-based vector search with NVIDIA GPU acceleration for index construction, we provide practical index build at high scale deployments.

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Index build time on a massive-scale vector database is a crucial pain point for the industry. In collaboration with NVIDIA, Kioxia demonstrated up to 20x improvement in AiSAQ index build time for high-dimensional vectors of 1024 dimensions, and up to 7.8x improvement in end-to-end build times. This 20x improvement represents a reduction from 28.4 days using CPU to 1.4 days using four NVIDIA Hopper GPUs to build the index, and a reduction from 31 days to 4 days in end-to-end testing.1

AI applications may now rely on larger volumes of vectorized information reaching tens of billions of vectors and beyond, stored on SSDs, while DRAM alone becomes impractical even at a billion scale. Kioxia enables a highly scalable storage architecture with AiSAQ technology by achieving billion-scale search, exceeding RAG application latency requirements using a single query server in a Milvus vectorDB environment powered by GPU acceleration on index builds that make large scale deployments practical.

“Vector databases provide a backbone for applications that need to understand intent, context, and similarity across massive, unstructured datasets in real time,” said Jason Hardy, Vice President, Storage Technologies, NVIDIA. “By leveraging GPU-accelerated indexing with the NVIDIA cuVS library, Kioxia supports high-dimensional vector databases that can scale and build indexes with unprecedented efficiency.”

First announced last year, KIOXIA AiSAQ open-source software technology addresses RAG scalability challenges by enabling vector search directly from SSDs, with reduced DRAM usage. AiSAQ technology provides high scalability, making it well-suited for both multi-tenant environments and large-scale monolithic index deployments. The technology leverages an innovative Global Index algorithm that combines hybrid clustering and graph search to deliver efficient vector search at extreme scale. With flexible tuning options to balance performance and high-volume vector scalability, AiSAQ software makes large-scale deployments more accessible and easier to expand.

“Scaling vector databases into the billions requires rethinking both memory and compute,” said Masashi Yokotsuka, Managing Executive Officer, Vice President, SSD Division, Kioxia Corporation. “By combining AiSAQ SSD-based vector search with NVIDIA GPU acceleration for index construction, we provide practical index build at high scale deployments. As industry innovators, we will continue to push the boundaries of AI using flash memory.”

Kioxia remains committed to advancing storage-driven AI solutions that support intelligent data processing at scale and continues to evolve AiSAQ capability toward trillion-vector deployments.

​​Kioxia will be demonstrating AiSAQ and other technology innovations at NVIDIA GTC booth #3522.

See the Kioxia blog for in-depth background on the index building system and testing: KIOXIA AiSAQ Achieves 4.8 Billion High-Dimensional Vector Search on a Single Server, with 7.8x Index Build Time Acceleration via GPUs.

Link to download KIOXIA AiSAQ open-source software: https://github.com/kioxia-jp/aisaq-diskann.

For more information, please visit www.kioxia.com, and follow the company on X and LinkedIn®.

About KIOXIA America, Inc.

KIOXIA America, Inc. is the U.S.-based subsidiary of Kioxia Corporation, a leading worldwide supplier of flash memory and solid-state drives (SSDs). From the invention of flash memory to today’s breakthrough BiCS FLASH™ 3D technology, KIOXIA continues to pioneer innovative memory, SSD and software solutions that enrich people's lives and expand society's horizons. The company's innovative 3D flash memory technology, BiCS FLASH, is shaping the future of storage in high-density applications, including advanced smartphones, PCs, automotive systems, data centers and generative AI systems. For more information, please visit KIOXIA.com.

© 2026 KIOXIA America, Inc. All rights reserved. Information in this press release, including product pricing and specifications, content of services, and contact information is current and believed to be accurate on the date of the announcement, but is subject to change without prior notice. Technical and application information contained here is subject to the most recent applicable KIOXIA product specifications.

Notes:

1. A total of 19.66 TB of vector data was processed for this benchmark. Performance or benchmark results may vary depending on the host device, read and write conditions, data sizes and other factors. KIOXIA AiSAQ Achieves 4.8 Billion High-Dimensional Vector Search on a Single Server, with 7.8x Index Build Time Acceleration via GPUs

NVIDIA is a trademark and/or registered trademark of NVIDIA Corporation in the U.S. and other countries.

Milvus is created and maintained by Zilliz.

LinkedIn is a trademark of LinkedIn Corporation and its affiliates in the United States and/or other countries.

Company names, product names, and service names may be trademarks of third-party companies.

Contacts

Media Contact:
Dena Jacobson
Lages & Associates
Tel: (949) 453-8080
dena@lages.com

Company Contact:
Mia Cool
KIOXIA America, Inc.
Tel: (408) 526-3087
mia.cool@kioxia.com

Kioxia America, Inc.


Release Summary
Kioxia has demonstrated high-dimensional vector search scaling to 4.8 billion vectors on a single server.
Release Versions

Contacts

Media Contact:
Dena Jacobson
Lages & Associates
Tel: (949) 453-8080
dena@lages.com

Company Contact:
Mia Cool
KIOXIA America, Inc.
Tel: (408) 526-3087
mia.cool@kioxia.com

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