LIVE Cheapest: GLM-4.7-Flash $0.000/Mtok in 153 models tracked Updated Jun 25, 2026
Jun 25, 2026
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Pricing / Cost Calculators / LLM API Cost for Chatbot Conversations

Cost to Power 10,000 Chatbot Conversations with LLM APIs

Calculate the real cost of using LLM APIs to power chatbot conversations. Compare all models for 10,000 conversations with verified per-million-token pricing.

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📊 Cost Summary

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Cost per conversations across 153 models

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ModelProviderInput $/MOutput $/MCost for 10K conversations

How this calculator works

Each chatbot conversation (multi-turn) requires ~3,000 input tokens (system prompt + conversation history + user messages) and ~1,000 output tokens (bot responses across multiple turns). Multi-turn conversations accumulate input tokens as context grows. Longer conversations with more turns will increase input tokens per conversation.

Formula: cost = (input_tokens × input_price_per_Mtok + output_tokens × output_price_per_Mtok) × quantity / 1,000,000

All prices are per million tokens, sourced directly from official provider pricing pages and verified by our automated scraper pipeline that runs 3× daily. No fabricated numbers — every price links to its source.

Frequently asked questions

How much does it cost to run 10,000 chatbot conversations with an LLM?

Powering 10,000 chatbot conversations costs $5-20 with budget models, $40-100 with mid-tier models, and $200-500+ with frontier models. Multi-turn conversations are input-heavy because the context window grows with each message. Models with prompt caching can reduce costs significantly.

Which LLM API is cheapest for chatbots?

DeepSeek V3, Gemini Flash, and Groq-hostalled models are cheapest for chatbots. For conversational quality, mid-tier models like GPT-4.1 Mini or Claude Sonnet provide better responses. Models with prompt caching (Claude, Gemini) can cut input costs by 50-90% for multi-turn chats.

How are chatbot token costs calculated?

Each conversation uses ~3,000 input tokens (context + history) and ~1,000 output tokens (responses). Total cost = (input_tokens × input_price + output_tokens × output_price) × number_of_conversations. Prices are per million tokens from verified provider pricing.