wzlxp.top builder tools Embedding calculator
Estimate embedding cost from document count, chunking strategy, average chunk size, model choice, and refresh frequency. Use this for indexing budgets before you add retrieval and LLM answer costs.
How to use
Enter document count, chunks per document, and average tokens per chunk based on your planned splitter.
Start with a smaller embedding model for cost planning, then compare with a larger model when quality needs justify it.
Use one-time, monthly, weekly, or daily refreshes to separate initial indexing cost from recurring embedding cost.
Embedding cost guide
Before RAG has query traffic, embedding cost is driven by how many chunks you create, how large those chunks are, and how often you regenerate them.
Documents are multiplied by chunks per document to estimate how many embedding requests your index needs.
Total chunks are multiplied by average tokens per chunk, then priced against the selected embedding model.
Cost per embedding run is multiplied by refresh frequency so one-time indexing is not confused with monthly spend.
A few hundred internal docs that are refreshed monthly during early product testing.
A help center with thousands of articles and weekly updates from support or documentation teams.
A high-volume corpus where chunk count and refresh frequency matter more than the price of one document.
References and assumptions
The first version uses manually maintained OpenAI embedding prices from the shared pricing data. It does not include vector database storage, vector search operations, reranking, LLM generation, or application infrastructure.
This page does not upload files or inspect documents. It estimates cost from numeric chunking assumptions so you can choose a reasonable indexing strategy before building a full RAG pipeline.
FAQ
It estimates how many embedding tokens are needed for a document corpus, the cost of one embedding run, and recurring monthly cost based on refresh frequency.
No. This page estimates embedding generation only. Use the RAG Cost Calculator when you also need retrieved context and LLM answer cost.
No. It uses numeric planning inputs only and does not upload files, text, API keys, or customer data.
The first version includes OpenAI embedding models because their prices are already maintained in this project. Other provider-specific embedding prices can be added after source coverage is ready.