Как да изчислим LLM Embedding Cost

Какво е LLM Embedding Cost?

The LLM Embedding Cost Calculator estimates the total expense of generating vector embeddings for text data using models like OpenAI text-embedding-3-small, Cohere embed-v3, or open-source alternatives. It helps developers budget for RAG pipelines, semantic search, and recommendation systems.

Формула

N

Number of Documents (documents) — Total text documents or chunks to embed

T_avg

Average Tokens per Document (tokens) — Mean token count per text chunk

P

Price per 1M Tokens ($/1M tokens) — Embedding model pricing rate

O

Overlap Ratio (0-0.5) — Fraction of overlapping tokens between consecutive chunks

Ръководство стъпка по стъпка

1. 1Enter the total number of documents or text chunks to embed
2. 2Specify the average token count per chunk (or paste sample text for auto-estimation)
3. 3Select the embedding model and its per-token pricing
4. 4View total cost for initial embedding plus estimated monthly re-embedding costs

Worked Examples

Common Mistakes to Avoid

• ✕Confusing embedding model pricing (per million tokens) with LLM inference pricing (per thousand tokens) — embeddings are orders of magnitude cheaper
• ✕Not accounting for chunking strategy — overlapping chunks increase token count by 10-30%
• ✕Forgetting to budget for re-embedding when documents are updated or the model version changes

Frequently Asked Questions