How AI Model Selection Affects Your Monthly Bill

How Platform Billing Works

Every AI request on the platform incurs two types of charges: an AI model fee (based on tokens used and the model's pricing) and a software fee (a flat 1 to 10 credits per request for the platform feature being used). The AI model fee varies dramatically by model. The software fee is the same regardless of which model you choose.

Credits are the platform currency: 1 credit = $0.001, so 1,000 credits = $1. When using platform-provided API keys, a 2x markup applies to the raw AI model cost. When using your own API keys, the AI model fee passes through at raw cost with no markup.

Monthly Cost Scenarios

Small Business Chatbot (500 conversations/month, 5 messages each = 2,500 messages)

• GPT-4.1-nano: ~0.5 credits/message = 1,250 credits = $1.25/month
• GPT-4.1-mini: ~3 credits/message = 7,500 credits = $7.50/month
• Claude Sonnet: ~4 credits/message = 10,000 credits = $10/month
• Claude Opus: ~15 credits/message = 37,500 credits = $37.50/month

For a small business chatbot answering FAQ questions from a knowledge base, GPT-4.1-mini at $7.50/month provides excellent value. Opus at $37.50/month is only justified if the chatbot handles complex sales conversations where tone quality directly impacts revenue.

High-Volume Support (5,000 conversations/month, 8 messages each = 40,000 messages)

• GPT-4.1-mini: ~3 credits/message = 120,000 credits = $120/month
• Claude Sonnet: ~4 credits/message = 160,000 credits = $160/month
• Mixed (nano for routing + mini for response): ~2 credits average = 80,000 credits = $80/month

At this volume, using a mixed-model approach saves $40 to $80/month compared to a single mid-tier model. Over a year, that is $480 to $960 in savings.

Data Analysis Workflow (200 reports/month)

• GPT o3-mini for analysis: ~15 credits/report = 3,000 credits
• Claude Sonnet for write-up: ~8 credits/report = 1,600 credits
• Total: 4,600 credits = $4.60/month

Even with a reasoning model for the analysis step, the total cost is under $5/month because the volume is moderate. At this scale, model choice matters less than at high volume.

The Biggest Cost Drivers

Volume

The number of requests per month has the biggest impact on your bill. A chatbot handling 100 conversations costs a fraction of one handling 10,000, regardless of model choice. If costs are too high, reducing unnecessary requests (better knowledge base to resolve questions in fewer messages) can be more effective than switching to a cheaper model.

Model Tier

Moving from premium to mid-tier models cuts AI costs by 60 to 80%. Moving from mid-tier to nano cuts costs by another 70 to 90%. But each downgrade reduces output quality, so test first to ensure the cheaper model still meets your standards.

System Prompt Length

A 1,000-word system prompt adds ~1,300 tokens to every request. At 10,000 requests/month, that is 13 million extra input tokens just from the system prompt. Cutting your system prompt in half saves real money at scale. See How to Reduce AI Costs.

Conversation Length

Each additional message in the conversation history adds to the input tokens of every subsequent request. Longer conversations cost progressively more per message because the growing history is re-sent each time.

Using Your Own API Keys

For users spending more than $50/month on AI model fees, connecting your own OpenAI or Anthropic API key removes the platform's 2x markup on AI costs. You pay the provider directly at their published rates, plus the platform's software fee per request. This can reduce your total bill by 30 to 40% at higher volumes.