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RAG & AI Search Cost Calculator
Calculate the cost of Retrieval-Augmented Generation (RAG) and AI-powered search.
How We Calculate This
RAG systems retrieve relevant context (3-5 document chunks ≈ 5,000 tokens) and combine it with the query (~1,000 tokens) to generate an answer (~1,000 tokens). A knowledge base or search product might handle 500 queries daily.
Frequently Asked Questions
How much does a RAG system cost to run?▼
At 500 queries/day, the LLM generation cost ranges from $15-200/month. Add embedding costs (~$2-5/month for retrieval) and vector database hosting ($20-100/month). Total: $40-300/month.
What is the cheapest model for RAG?▼
Gemini 2.0 Flash and DeepSeek V3 offer the best value for RAG. Their large context windows and low pricing make them ideal for knowledge-heavy applications.
Do I need a vector database for RAG?▼
For production RAG, yes — vector databases (Pinecone, Weaviate, pgvector) enable fast semantic search. For prototypes, you can load documents directly into a large-context model.