What are reasoning tokens?

OpenAI's o-series models think internally before answering, producing reasoning tokens that are discarded from the response but still billed at the output rate. They can be several times larger than the visible answer, especially on hard tasks.

How big is the hidden overhead?

It varies a lot by task. Simple questions may add a small amount, while hard multi-step problems can produce reasoning that dwarfs the answer. This calculator uses complexity-based multipliers as a planning estimate, not a guarantee.

Can I control reasoning token usage?

The o-series exposes a reasoning effort setting on some models, and you can reserve a max-completion-tokens budget that includes reasoning. Choosing a lighter model like o3-mini for easier tasks also reduces the hidden cost.

Does this tool call OpenAI?

No. It estimates entirely in your browser using published pricing and complexity heuristics. Nothing is sent to OpenAI, stored, or logged.

o1 Reasoning Token Cost Calculator

o1 reasoning token cost calculator

OpenAI’s reasoning models (o1, o3, o3-mini) think before they answer, and that thinking is generated as reasoning tokens. You are billed for those tokens at the output rate, but they never appear in the response — so the bill is larger than the visible answer suggests. This calculator estimates that hidden overhead by task complexity and shows your true cost per call.

How it works

You enter your visible prompt tokens and the answer tokens you expect to read. Picking a task complexity applies a multiplier to estimate the hidden reasoning tokens — light for simple lookups, much heavier for hard multi-step problems. The calculator prices the prompt at the input rate, then prices the answer plus the hidden reasoning at the output rate, revealing both the naive visible-only cost and the realistic true total cost.

Tips and notes

The invisible tokens dominate on hard tasks. On complex reasoning, the hidden tokens can be several times the answer — budget for them.
Match the model to the task. Use o3-mini or a non-reasoning model for easy work; save the heavy reasoning models for problems that actually need them.
Use the reasoning-effort and token caps. Where the API exposes them, they bound the hidden cost directly.
Estimates, not invoices. Actual reasoning length is non-deterministic; treat the output as a planning figure and confirm with your usage dashboard.