Blackwell enables Zilliz Cloud to support real-time vector similarity search at enterprise scale, with millions of QPS, sub-millisecond latency, and multimodal embedding support.
Real-Time Multimodal Search
Zilliz Cloud on Blackwell handles streaming embeddings (text, images, video) at millions-per-day throughput. E-commerce platforms search product catalogs by visual similarity instantly. Content platforms retrieve articles by semantic + visual relevance simultaneously.
Sub-Millisecond Query Latency
Blackwell's 800 GB/s memory bandwidth and fifth-generation Tensor Cores reduce similarity search latency to single-digit microseconds per query. Zilliz Cloud queries return sub-millisecond for 10M+ vector collections, enabling real-time personalization and recommendation without cached response tricks.
Enterprise-Scale Throughput
Zilliz Cloud on Blackwell sustains millions of queries per second per cluster. Healthcare platforms search patient embeddings for rare disease cohorts instantly. Financial institutions correlate trading signals against historical embeddings in real-time.
Hybrid Search Results
Zilliz Cloud can combine vector similarity with metadata filtering, keyword search, and reranking at Blackwell GPU speed. Queries return highest-relevance results ranked by multiple signals simultaneously.