AI Agent Cost Estimator

Understanding AI Agent Cost Structures

AI agents are more expensive than simple API calls because they make multiple LLM calls per interaction (tool use, reasoning loops, RAG retrieval). A single user query might trigger 3-10 LLM calls internally. Understanding each cost component helps you optimize spending and choose the right model for each task.

Model Selection Matters Enormously

The cost difference between models can be 100x or more. GPT-4o Mini costs roughly $0.15 per million input tokens versus GPT-4 at $30. For many agent tasks (routing, classification, simple extraction), smaller models perform nearly as well. Use expensive models only where quality demands it, and route simpler subtasks to cheaper models.

Hidden Costs: Orchestration and Human Oversight

Platforms like LangChain Cloud, CrewAI, or custom orchestration layers add fixed monthly costs. Vector databases for RAG (Pinecone, Weaviate, Qdrant) scale with data volume. And the most overlooked cost is human oversight: reviewing agent outputs, handling failures, and maintaining prompt chains. Budget 10-20 hours per week minimum for production agents.