About this Embedding Storage Calculator
Embedding storage is driven by chunk count, vector dimensions, byte precision, metadata, indexing overhead, and replicas.
Who this calculator is for
- AI engineers planning RAG ingestion.
- Developers comparing embedding dimensions.
- FinOps teams estimating vector storage before vendor selection.
When to use it
- Estimate storage before embedding a document corpus.
- Compare dimensions or quantized byte sizes.
- Add metadata, index overhead, and replicas.
How to use this calculator
- Enter documents and chunks per document.
- Set dimensions, bytes per dimension, and metadata bytes.
- Add index overhead, replicas, and storage price.
- Review billable storage and monthly cost.
Key assumptions
- Uses 1024^3 bytes per GB.
- Pricing and overhead are user-entered.
- No document or embedding data is uploaded.
Accuracy and testing
Review formula sources, default test cases, assumptions, unit handling, rounding rules, and changelog for this calculator.
How this calculator works
Vectors = documents x chunks per document. Raw bytes = vectors x (dimensions x bytes per dimension + metadata bytes). Billable GB applies index overhead and replicas.
Vectors = documents * chunks per document. Raw storage GB = vectors * (dimensions * bytes per dimension + metadata bytes) / 1024^3. Billable GB = raw GB * (1 + overhead percent / 100) * replicas.
Inputs explained
Documents and chunks
Corpus size after chunking.
Dimensions and byte precision
Embedding size and storage precision, such as float32 or quantized values.
Overhead and replicas
Index structures and redundancy that increase billable storage.
Understanding your results
Billable storage is the planning number for infrastructure cost. Raw vector storage helps explain how much overhead the database layer adds.
Example scenarios
Knowledge base corpus
50,000 documents with four chunks each at 1,536 dimensions can exceed 1 GB before metadata and replicas.
Key Features
- Instant Calculation
- Private & Secure
- Mobile Optimized
Tips & Best Practices
- Use the RAG chunk calculator first to estimate chunks.
- Quantization can reduce storage but may affect retrieval quality.
- Include metadata carefully because it can be large at scale.