Chatbot cost

The simplest stack of the eight — one model, many turns. The cost driver isn't the token price; it's how much context you re-send on every turn.

Conversations per day

Model

Model turns per conversation

Context tokens per turn (in) history + system prompt + user message

Reply tokens per turn (out)

Platform / hosting $/month (chat widget, session storage)

The formula

llm = convos × turns × (tokIn/1M × P_in + tokOut/1M × P_out) × 30 total = llm + platform per_convo = total / (convos × 30)

Token prices as of . Context grows with conversation length — the per-turn input default assumes a mid-conversation turn, not turn one. Prompt caching (re-sending the same long system prompt) can cut 30–70% off this number; excluded here as the conservative case. Human escalation costs are the real tail risk: one human-handled conversation can cost more than 100 automated ones.