How much storage do 1 million embeddings require?

1M embeddings at 1536 dimensions (OpenAI ada-002) in FP32 = 6 GB. In FP16 = 3 GB. At $0.023/GB/month (S3 standard) that's $0.07–$0.14/month—storage is rarely the bottleneck vs retrieval costs.

Should embeddings be stored in FP16 or FP32?

FP16 is sufficient for most retrieval tasks with negligible recall loss. FAISS can further quantize to INT8 or PQ codes, reducing storage by 4–32× with minimal recall degradation.

Embedding Storage Cost Calculator

Calculate monthly cloud storage cost for embedding vectors. Enter number of documents, embedding dimension, precision, and cloud storage pricing ($/GB/month) to get total cost.

Networking

Algorithms

Binary & Number

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Dev Metrics

IP Subnet Calculator

IP Address

CIDR Prefix

Network

192.168.1.0

Broadcast

192.168.1.255

Subnet Mask

255.255.255.0

First Host

192.168.1.1

Last Host

192.168.1.254

Usable Hosts

254

Binary breakdown:

IP: 11000000.10101000.00000001.00000000

Mask: 11111111.11111111.11111111.00000000

Net: 11000000.10101000.00000001.00000000

How to Use

Enter the values for the patient or scenario you are assessing. Calculate monthly cloud storage cost for embedding vectors. Enter number of documents, embedding dimension, precision, and cloud storage pricing ($/GB/month) to get total cost. Use the embedding storage cost result to inform your clinical assessment.

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Embedding Storage Cost Calculator

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Frequently Asked Questions

How much storage do 1 million embeddings require?

Should embeddings be stored in FP16 or FP32?