zai earnings transcript was a really good read, a list of interesting points (mostly verbatim from the transcript): * Chat → Coding → Agent …

zai earnings transcript was a really good read, a list of interesting points (mostly verbatim from the transcript): * Chat → Coding → Agent → Cowork → Autonomous AI * What truly matters is who can continuously bring stronger models to market at a faster pace and at a better cost. * Cybersecurity is currently the clearest validated direction and progressing the fastest. Legal services, finance, data analysis, and other fields are also being explored, but remain at an early stage and have not yet generated revenue at scale; their commercialization timelines will differ because their reliability thresholds and verification mechanisms are different. * In the first half of 2026, total revenue reached US142 million, representing year-on-year growth of nearly 400%, and is now generated primarily by the open platform and API business. * As of the end of August 2026, our ARR had reached US1.6 billion. This ARR is calculated by annualizing monthly revenue—that is, by multiplying August revenue by twelve. Frontier-model companies overseas and some companies in the industry also use a more aggressive method, multiplying the latest week's data by 52. Taking the ramp-up of GLM-5.3 into account, ARR under that method has already exceeded US2 billion. * historic surge in platform revenue was driven mainly by model capability rather than relying entirely on price elasticity. * Gross margin for the open-platform and API business rose from negative 0.4% in the first half of last year to 24.6% in the first half of this year * Adjusted net loss in the first half of this year was approximately US292 million, lower than R&D expenditure (US317 million) — i.e. gross profit now covers admin and selling expenses, so "the business has started to self-fund R&D." But it's covering less than 10% of it; the other ~90% of R&D is funded by the balance sheet. * Compute multiplier (API revenue generated for every dollar invested in compute) increased fourteenfold compared with the first half of last year * As of August 2026, the platform had more than 7.4 million registered users, up 144% from the beginning of the year. Paying daily active users increased by 603%. * As of the end of August, on an ARR basis, the numbers of high-quality user cohorts contributing more than US100,000, US500,000, US1 million, US10 million, US25 million, and US$250 million on an annualized basis were, respectively, 115, 25, 37, 8, 2, and 2. * Total usage over six days exceeded 62 trillion tokens, driving overall platform usage up by more than 20%. (roughly 5,000 B300 GPUs worth of capacity I think) * Zhipu has invested over the long term in data and training-environment development, including a data-annotation team of several hundred people. One important reason GLM-5.3 improved substantially over GLM-5.2 is that the scale of its data environments expanded by several dozen times. * Data is beginning to generate itself. Model-versus-model self-play pipelines mean that the upper bound of data quality is no longer determined by the speed of human annotation, but by the model's own ability to verify results. https://x.com/i/article/2094542324617658368

Source: Soumith Chintala (X) | 2026-09-03

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