The price moved
The average price of a token fell 41 per cent, and the reason is that buyers left the frontier
Frontier models took 53 per cent of American corporate AI spend in early August and 45 per cent by September. Ramp’s index is not measuring vendors discounting. It is measuring buyers leaving, and two of the cheap tiers they left for raised their prices this week.
| What | Before | After | Source |
|---|---|---|---|
| US blended effective, per M | $1.15 in March | $0.68 | measured by Ramp |
| GLM-5.3-Flash input, per M | $0.075 | $0.15 | Z.ai rate card, 9 Sep |
| GLM-5.3-Flash output, per M | $0.25 | $0.50 | Z.ai rate card, 9 Sep |
| Solar Pro 4 input, per M | $0.03 | $0.09 | Upstage rate card, 11 Sep |
| Solar Pro 4 output, per M | $0.12 | $0.36 | Upstage rate card, 11 Sep |
The effective price American companies pay per million tokens fell from $1.15 to 68 cents between March and September, Ramp said Wednesday.
That fall is not a discount. It is the record of buyers walking down the price ladder, and Ramp can see them doing it.
Ramp’s index measures what its corporate card and bill-pay customers were actually charged, not what any vendor lists. A company that moves a summarisation job off a frontier model and onto a mid-tier one drags that index down without a single rate card changing. The substitution is visible directly rather than by inference: the share of usage going to frontier models fell from about 53 per cent in early August to 45 per cent by September.
The concentrated end of the market moved first and moved hardest. The top 1 per cent of spenders, the cohort Fortune reports drives about 80 per cent of OpenAI’s and Anthropic’s enterprise revenue, cut per-employee spend by nearly 10 per cent in August. That is the buyer with the most leverage and the most engineers, deciding it was overpaying.
Split by vendor, the same index shows a race running at two speeds. Since 1 August OpenAI’s effective price fell 38 per cent to 48 cents and Anthropic’s fell 22 per cent to 90 cents, leaving a gap of nearly two to one between two companies selling into the same procurement decision. Anthropic has held a floor near 90 cents since June while OpenAI’s number kept sliding. OpenAI’s finance chief Sarah Friar told a Goldman Sachs conference on Tuesday that the company had cut GPT-5.6 Luna’s price by 80 per cent since launch, which she placed below some Chinese open-weight models.
The obvious objection is that Ramp is measuring its own customers, and it is. That is the correct reading of the number rather than a defect in it. This is American corporate card and bill-pay spend, so it is strong evidence about what buyers chose and no evidence at all about what anyone lists. Khazarian, Ramp’s chief economist, gave Fortune the mechanism in a line: “prices are relative to the other products available on the market,” and the mid-tier products “are also really good.”
The verdict for anyone with a 2026 cost model: the number that changed is the one on your invoice, not the one on a pricing page, so re-derive your unit economics from billing data and then check the rate cards separately. Both of the cheap tiers this paper could read a rate card for went up this week.
What it changes Pull your last three months of API invoices and compute your own blended price per million tokens. If it fell, find out which workloads moved down a tier and whether anyone decided that on purpose. Then check whether the tier they moved to still costs what it did in August.
Ramp’s figure is drawn from its own corporate card and bill-pay customer base, so it measures US corporate buying behaviour and not global API pricing. Ramp’s sample size and industry mix are not published. Fortune spells the chief economist’s surname two ways in the same piece.