AI Interactive Tools
RAG Cost Estimator
Estimates vector DB + LLM token + embedding + infrastructure costs monthly & yearly. Compares Pinecone, Weaviate, Qdrant, pgvector.
TL;DR
One-line answer: Vector DB, LLM, embedding and infra are estimated separately.
- Compares Pinecone, Weaviate, Qdrant, pgvector + 5 LLMs + 4 embeddings.
- Monthly + yearly projection plus a 12-month trend.
- 5 cost-cutting recommendations tailored to your inputs.
Definition
- RAG Cost
- The total monthly cost of a Retrieval-Augmented Generation system, summing vector DB, embedding generation, LLM token consumption and operational infrastructure.
- Also known as: RAG cost, retrieval cost, vector DB cost
Inputs
Monthly estimate
Vector DB
$20
LLM
$2100
Embedding model
$6
Infrastructure
$90
Total
$2,216
/ month · $26,592 / year
5 optimisation tips
- LLM dominates cost. Try prompt caching, switch to a smaller model for retrieval-only steps, and reduce max_tokens.
- Cache deterministic queries with a 1-hour TTL.
- Audit re-ranker spend; smaller open-source rerankers cut 40%.
- Negotiate annual commit pricing with your LLM vendor (~10-25% off).
- Set per-tenant token caps to prevent surprise bills.
Pricing values are based on Q1 2026 public lists; estimates only. May vary by contract.
References
- Pinecone Pricing, Pinecone Systems
- OpenAI API Pricing, OpenAI
- Anthropic API Pricing, Anthropic
- Qdrant Cloud Pricing, Qdrant