A cheaper AI model has arrived. Is the finished job cheaper?

The price tag belongs to a particular kind of use

Imagine you help a school club turn a few receipts into a spending sheet. Someone offers you a cheaper assistant. Before switching, you need to know two things: can you open the relevant tool, and can you check the sheet it produces? A low price is useful only when it leads to work you can use.

OpenAI introduced GPT-6.1 Terra on 26 October, describing improvements in visual reasoning, computer use and writing. That suggests a possible role in reading a small document or working through a screen. It still leaves you with a practical choice: try one bounded task before connecting it to a real workflow.

Two prices, and a small calculation

A token is a small piece of text counted by a model service. It is not always a whole word. Input tokens are the material the service reads; output tokens are what it generates, including billable reasoning where applicable. A consumer subscription usually gives an allowance, while an API lets software call a model and pays according to usage.

For a fictional standard API request, assume 10,000 uncached input tokens and 2,000 total billable output tokens. At the listed rates, reading costs 10,000 divided by 1,000,000, multiplied by US$1: US$0.01. Writing costs 2,000 divided by 1,000,000, multiplied by US$5: another US$0.01. Together that is US$0.02. These assumed token counts are not a measured invoice task. Tools, cache writes, retries, taxes and long-input adjustments are outside this example.

Now imagine that you have to correct three cells afterwards. The two-cent calculation stays correct for that one assumed request, but it says nothing about your checking time or any additional calls. When comparing assistants, keep a second column for whether you accepted the result and what you repaired. That is how a cheap answer becomes a meaningful cost comparison.

Make the answer checkable before asking

Here is a fictional club purchase: three pencils at £2 each, and two notebooks at £4 each. Delivery is not stated. Write those facts on paper or in a small local text file. Keep the original separate from the working copy. These pounds describe the invented purchase; the dollar rates above describe a separate API example.

Ask an assistant to return the item, quantity, unit price and line total, followed by a goods subtotal and a delivery field. You can predict the answer yourself: three times two is six; two times four is eight; six plus eight is fourteen. The goods subtotal is £14. Delivery remains UNKNOWN. A polished grand total that silently assumes free delivery has changed the task.

First try the text. If your existing tool accepts images, make your own legible picture of the same fictional note and repeat it. Compare the cells with the original rather than judging how convincing the explanation sounds. Record the product surface and visible model; a text trial and an image trial test different inputs.

Let a mistake leave something useful

Try a second version with the delivery line blank and a third with the notebook quantity changed from two to three. Predict £18 for the third goods subtotal: £6 for pencils plus £12 for notebooks. A useful check catches the changed quantity while preserving the missing delivery information. An assistant that repeats £14 has carried an old answer into a new case.

Keep a small record with the input version, expected cells, observed cells, repairs and unresolved fields. Expected answers can be filled in now; observations wait for a real trial. If the tool stops midway, keep the checked rows and the point where it stopped. Someone else can continue from that smaller piece of work.

Your first deliverable can be this fictional receipt-checking sheet, with its three inputs and expected results. A real club could later decide whether a similar workflow helps, using its own authorised records. Keep approval of spending and payments with the person responsible for them. You can learn whether the extraction is useful without giving an assistant permission to move money.