Key Takeaways
- One token is approximately 4 characters or 0.75 words in English. Non-English languages use more tokens per word.
- Token count determines cost, speed, and context limits for every AI API call.
- Optimizing token usage (shorter prompts, efficient formatting) can reduce AI costs by 30-50% without sacrificing quality.
Token Economics: Understanding AI Costs
AI API pricing is based on tokens processed. Understanding token economics helps forecast and optimize costs:
- Input tokens (your prompt + context) are typically 2-5x cheaper than output tokens (the AI's response).
- System prompts consume tokens on every request. A 500-word system prompt adds ~375 tokens to every API call.
- RAG context adds tokens. Retrieving 5 document chunks of 300 words each adds ~2,250 tokens per query.
- Conversation history grows with each turn. Summarize or truncate history to manage costs in multi-turn conversations.
Cost Estimation
For a customer support chatbot handling 10,000 conversations/month with average 4 turns each: ~40,000 API calls x ~2,000 tokens average = 80M tokens/month. At GPT-4o pricing ($5/M input, $15/M output), this costs approximately $400-800/month.
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