Editorial Team
5 min read
Cambricon reported 5.996 billion yuan in first-half revenue and 2.311 billion yuan in net profit, but its unaudited filing also shows 8.25 billion yuan of inventory and a 65.83% fall in operating cash flow. The result demonstrates commercial demand for domestic AI hardware; sustaining it depends on supply, product execution and customers’ willingness to keep deploying its systems.
Cambricon Technologies, a Shanghai-listed, fabless Chinese designer of AI chips and system software for cloud servers, edge devices and terminals, has delivered its best interim result since its listing. Its chairman and general manager, Chen Tianshi, previously spent more than 20 years researching AI and processor chips at the Chinese Academy of Sciences’ Institute of Computing Technology before founding and leading the company. That technical lineage matters because Cambricon is selling a hardware-and-software platform, not an end-user AI service.
The immediate result is striking. But its value as evidence of a durable domestic champion is more limited: Cambricon’s own filing flags supplier stability, inventory valuation and fast technical change as risks, while its biggest peers are also reporting rapid demand.
Cambricon-reported first-half year-on-year growth in revenue and net profit. Source: Shanghai Stock Exchange filing.
In its unaudited half-year filing, Cambricon reported 5.996 billion yuan in revenue for the six months to June 30, up 108.13% year on year. Net profit attributable to shareholders was 2.311 billion yuan, up 122.61%; profit excluding non-recurring items was 2.166 billion yuan, up 137.30%.
The company said steadily rising AI-computing demand and deeper work with leading finance and internet businesses drove the increase. It said its products had passed full production-environment validation for domestic mainstream AI applications. Those are company statements, not a customer-by-customer revenue breakdown, but the filing describes deployments in finance, internet, electric power, mining, cities and retail.
Second-quarter net profit was 1.298 billion yuan, following 1.013 billion yuan in the first quarter, a 28% sequential increase, the report said. A separate report put second-quarter revenue at 3.1 billion yuan, in line with a 3-billion-yuan Bloomberg-poll consensus estimate; the first report put the half-year gross margin at 55%.
The earnings figure is not the only measure of the half. Net cash generated by operating activities fell to 311.3 million yuan from 911.2 million yuan a year earlier, a 65.83% decrease. Cambricon attributed the change to higher external purchases and tax payments.
Inventory reached 8.248 billion yuan at June 30—45.32% of total assets and 66.83% above the previous year-end—principally because raw materials and outsourced-processing materials increased. Prepayments for purchases were 2.914 billion yuan, up 291.37%. The company says it bases procurement on customer orders and its forecast of future demand; it also warns that a changed market could force inventory write-downs and harm profitability.
That is not evidence that the inventory is impaired. It is the financial condition that must be met for the sales surge to translate into repeatable cash generation.
Cambricon designs chips but does not manufacture them itself. Its cloud products include chips, accelerator boards and servers; it also sells edge products, processor intellectual-property licences and a common software platform. The filing says its intelligent-computing clusters combine its boards or servers with partners’ server, network and storage equipment for customers that need a full deployment rather than a single server.
It spent 702.5 million yuan on R&D in the half, 29.63% more than a year earlier. The R&D team numbered 1,007 people, or 80.62% of the workforce. It is developing a next-generation intelligent-processor microarchitecture and instruction set, while updating distinct software platforms for training and inference. The filing says its current software has been adapted for models including DeepSeek, Qwen, GLM, Kimi and MiniMax; that compatibility is a company-reported capability, not a comparative benchmark against rival hardware.
The supply constraint is broader than a generalized shortage. Cambricon says its fabless model depends on IP licensors, server suppliers, wafer fabricators and packaging-and-test providers. It also says its inclusion, along with some subsidiaries, on an entity list can create a risk to supply-chain stability and that switching suppliers carries costs. The company says it will seek to mitigate that through its own technology and industry relationships; the filing does not quantify available capacity or name suppliers.
China’s push for technology self-sufficiency and U.S. export controls limiting access to advanced accelerators have created an opening for domestic designers, the report said. Cambricon’s filing itself says Nvidia still has an absolute global lead in AI chips and that more established semiconductor companies and start-ups are entering the field.
The domestic numbers likewise do not make Cambricon’s result a solo phenomenon. Beijing-based Moore Threads forecast first-half revenue of as much as 1.75 billion yuan, up as much as 149% year on year, while Hygon Information Technology forecast up to 9.3 billion yuan, up 70%, the report said. Those are forecasts, whereas Cambricon has reported actual results, so they are signals of demand rather than like-for-like performance rankings.
Cambricon has raised the management benchmark, too. In July it set a target of more than 100 billion yuan in cumulative revenue over the three years to 2028, linked to a new employee stock-incentive plan, versus a prior 4.6-billion-yuan cumulative target for 2024 through 2026, the report said. A stock-plan target establishes management’s incentive and ambition; it is not an independently validated forecast.
Morgan Stanley analysts, cited in that report, said peers’ second-half launches could test Cambricon’s relative performance and price-to-performance positioning. That is the comparison the next product cycle must answer.
The next disclosures need to clarify whether procurement is turning into delivered, cash-generating deployments rather than a precautionary build-up. Useful evidence would include the evolution of inventory and operating cash flow, the scale and repeatability of orders, and the launch timing and performance of the processor now in development.
For now, the filing proves that domestic AI-computing demand has become nearly 6 billion yuan in six-month sales for Cambricon. It does not establish that the company can protect price, supply or software adoption as alternatives multiply. The balance between those operating measures—not the revenue headline alone—will decide how much strategic leverage the record half has created.
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