A single chatbot interplay could devour a couple of thousand tokens. A helpful agentic workflow can devour a whole bunch of 1000’s or hundreds of thousands of tokens per day as a result of it does greater than reply a query. It decomposes the issue, retrieves context, causes by choices, invokes APIs, checks the output, and infrequently runs a number of passes earlier than reaching a outcome. Subsequently, the economics must be understood on the degree of “agent cases,” not simply mannequin calls.
For the estimates under, I’m utilizing a blended token price of $3 {dollars} per million tokens. This isn’t supposed to mirror a single vendor’s record worth. It’s a blended planning determine that assumes a mixture of enter and output tokens, reasoning steps, retrieval-augmented technology, summarization, instrument calls, reminiscence updates, and occasional use of bigger context home windows. Some enterprises pays much less by quantity reductions or by routing work to smaller fashions. Others pays extra by utilizing premium fashions, long-context prompts, internet shopping, massive doc ingestion, and repeated reasoning loops.
The essential method is easy. If an agent consumes 2 million tokens per day, it consumes 730 million tokens per 12 months. At $3 per million tokens, that single agent prices about $2,190 per 12 months in token burn. That quantity sounds surprisingly low till you multiply it by the variety of brokers, workflows, and customers, plus the encompassing infrastructure required to run these methods safely.
What an agent actually prices
Within the mannequin used right here, the annual token-only price per agent ranges from about $1,095 to $3,833, relying on the use case.