Zhipu said its model-as-a-service business posted sharp gains in both usage and monetization over the first half of the year. By the time the earnings report was released, token calls on its MaaS platform had risen more than 40 times from the start of the year, while paid daily active users increased 603%. The company also said average daily usage among its top 10 clients surged 98 times.
The increase did not come from discounting. Zhipu said the average selling price of its API rose about 101% year over year in the first half, and subscription pricing for its Coding Plan was also raised. With both volume and pricing moving higher, revenue from the open platform and APIs reached 825 million yuan, up 2735.7% from a year earlier.
The earnings report also introduced a custom metric called the "compute multiplier," which measures how much API revenue is generated for every 1 yuan of compute cost. Zhipu said that figure improved about 14 times year over year in the first half.
Zhipu said its API business did not just post a jump in revenue over the past six months. Usage and commercial efficiency both moved higher as well.
By the time the earnings report was released, token calls on the company’s MaaS platform had increased more than 40x from the start of the year. Paid daily active users were up 603%, and the average daily call volume from Zhipu’s top 10 clients rose 98x.
The company said the growth was not driven by lower pricing. In the first half, Zhipu’s average API selling price increased about 101% year over year, and subscription pricing for its Coding Plan was also raised. With both volume and pricing climbing, revenue from the open platform and APIs reached 825 million yuan, up 2735.7% from a year earlier.
Zhipu also disclosed a custom metric in its earnings report called the “compute multiplier,” used to measure how much API revenue is generated for every 1 yuan spent on compute costs. In the first half, that metric improved about 14x year over year.
Put simply, Zhipu said it sold more tokens while also generating much more revenue per unit of compute than it did a year earlier.
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