RAG Chatbot — 10,000 Monthly Active Users
Monthly LLM API cost for a RAG-powered chatbot serving 10,000 MAU, with typical conversation patterns.
Assumptions
- 10,000 MAU, avg 8 conversations/user/month = 80,000 conversations
- Avg 6 turns per conversation
- System prompt: 1,500 tokens
- RAG context: 3 chunks × 500 tokens = 1,500 tokens
- User message: 150 tokens avg
- Assistant response: 400 tokens avg
- Total input per turn: ~3,150 tokens (system + RAG + history + user)
Base model: Claude Sonnet 5 — $3/M input · $15/M output · 2026-08-19
Cost breakdown by component
How to cut this cost by 50%+
These are estimates based on typical patterns. Enter your specific token counts and volume for a precise calculation.
Frequently Asked Questions
What does a RAG chatbot cost for 10,000 users?
Roughly $5,000–$11,000/month on Claude Sonnet 5, depending on conversation length and RAG chunk count. The biggest lever is conversation history — each additional turn adds all previous turns to input. Enable prompt caching and limit history to 5-7 turns to reduce costs by 50%+.
What is the biggest cost driver in a RAG chatbot?
Conversation history, which grows quadratically per conversation. By turn 6, you're resending 5 full turns of dialogue as context. The second driver is the number of RAG chunks per query — retrieving 10 chunks instead of 3 triples that cost line.
Pricing verified 2026-08-20. All figures are estimates with stated assumptions. See methodology.