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What are the costs to run AI Agents?
Tokens, models, and pricing — what drives agent costs and how to keep them predictable.
Key takeaways
You pay per token — the text the model reads and writes
Simple agent interactions cost fractions of a cent
Match model size to task complexity to optimize spend
Full cost visibility prevents surprise bills
How pricing works
AI agents run on language models, and language models charge per token — the units of text they read (input) and generate (output). A token is roughly ¾ of a word. The cost per token varies by model: smaller models like GPT-4o mini cost fractions of a cent per thousand tokens, while larger models like Claude 3.5 Sonnet cost more but handle complex reasoning better.
What a typical agent costs
A simple support agent handling a short conversation might cost $0.001–$0.01 per interaction. A research agent processing long documents could cost $0.05–$0.20 per run. At scale, a support agent handling 10,000 conversations per month might cost $10–$100 in model fees — a fraction of what a human team costs.
Controlling costs
Use smaller models for simple tasks and reserve powerful models for complex reasoning. Set token limits and guardrails to prevent runaway conversations. Cache common responses. Agent Studio gives you per-agent, per-conversation cost breakdowns so you always know where money is going.