How to Run 25 Million Image Vectors on Under 1GB of Memory in Milvus

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This post details how to run 25 million image vectors on under 1GB of memory in Milvus. It explains why AISAQ and IVF_FLAT indexes failed for this workload and how the simplest FLAT index, combined with FP16 vector storage, mmap for raw vector data, and scalar filtering before vector comparison, achieved low memory usage and good latency. It also provides guidance on when this pattern is applicable and how to interpret Milvus Sizing Tool estimates.