Unverified50% confidenceFactExact time
Under float32 storage, each 1024-dimensional vector occupies 4KB, so an index of a million-scale documents requires at least 4GB of storage.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedStoring 100 million 1536-dimensional OpenAI embedding vectors in float32 requires approximately 600 GB of memory, which can be compressed to approximately 150 GB after 8-bit scalar quantization.77% similarUnverifiedA fully in-memory autocomplete solution requires several GB to tens of GB of memory to store 240 million domain name entries.76% similarUnverified一张1024×1024的未压缩RGBA纹理占据4MB存储空间76% similarUnverifiedA computer with a 32-bit address bus can address at most 2³², approximately 4.3 billion memory addresses (i.e., 4GB), which is the reason for the 4GB memory limit in early 32-bit operating systems.75% similar
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