“The Cards Are Here. Now What?”

That may be the most painful question countless companies have faced over the past two years amid China’s sweeping push for domestic computing power.

Not long ago, competition among Chinese AI chips was still about spec sheets and benchmark scores. But in 2026, computing power is no longer a cold hardware term tucked away in a server room. It has become an invisible form of productivity running through industries across the economy.

The market logic is now shifting fast:

Performance metrics are only the ticket in. Whether a chip can solve real business problems and lower the barrier to adoption has become the line that determines the value, and even the fate, of an AI chip.

At this critical point, as Chinese computing power moves from “technically usable” to “usable in real-world scenarios,” Xinqiao Semiconductor, a young Beijing-based Chinese GPU startup, has entered the field with an unusually pragmatic playbook.

Beyond Benchmarks: From Domestic Chips to a Computing Power Foundation

As demand for computing power shifts from experimental testing to scaled production, the way China evaluates AI chips is being rebuilt.

Xinqiao Semiconductor was founded in March 2025, less than a year ago.

Its founding team brings together several industry veterans with long experience in semiconductors. Founder and chairman Han Xiao has spent years in IDC and AI data center systems integration, while co-CEO Xiao Ronghui also has years of experience in industry research and the semiconductor sector.

That team DNA, rooted in deep industry experience and an emphasis on real deployment, has shaped a pragmatic product roadmap. Xinqiao has already launched its Sinexus X200 and S200 series of high-performance Chinese GPGPU products.

These chips are not lab prototypes. They are mass-production-grade products built for core use cases such as AI training and inference, and have already completed deployment validation in multiple AI data center clusters.

Xinqiao’s edge is that it does not simply offer a chip with self-owned intellectual property. Using that chip as the starting point, it has built a full-stack domestic AI data center cluster solution.

This kind of engineered, system-level delivery capability helps address the trust questions large government, enterprise and carrier customers face when building a domestic technology foundation: whether they dare to use it, whether it works, and whether they will keep using it after the first deployment.

Rejecting “Delivery Means the End”: Rebuilding the Full-Lifecycle Logic

Zhang Xin, director of AI solutions at Xinqiao, described the pain point in the current localization push:

What the industry truly lacks is not just computing power equipment, but the ability to use computing power well.

For a long time, the AI chip industry has operated under a “box model”: once the hardware is delivered to the customer, the contract is considered complete.

Xinqiao is rejecting that model. Instead, it focuses more on the long-term usability and operational value of Chinese computing power in real-world scenarios, stressing that chips and computing power must be deeply integrated with business needs.

For example:

Manufacturing companies: deploying visual inspection applications so computing power directly participates in production, reducing false positives and missed defects in manual inspection, and turning cost optimization into immediately visible gains;

Medical institutions: using Chinese computing power to support imaging analysis platforms, enabling assisted diagnosis and shortening screening cycles;

Education: building intelligent exam-grading systems on computing power, reducing teachers’ workload while improving processing efficiency.

Based on this view, Xinqiao’s full-stack solution covers the entire lifecycle, from early planning and design to platform deployment and later operations and maintenance. It can better fit government procurement processes and domestic compliance requirements, avoiding the traditional “equipment delivery means the end” model.

The logic behind this shift is that decision-making power over computing power is moving from IT teams to business departments.

In the past: procurement-driven. Buy the cards first, then figure out what they can do. Computing power was a fixed asset in the back office.

Now: value-driven. Every watt of resource must participate in the business and create value. Computing power is front-office productivity.

Zhang Xin summed it up this way: future competition will depend not only on who has more computing power, but on who can make that computing power run more efficiently and generate higher returns.

Entering the Main Battlefield: Closing the Loop Between Industry Adaptation and Commercial Monetization

In response to these industry shifts, Xinqiao is focusing on the long-term usability and operational value of Chinese computing power in real-world scenarios, emphasizing that chips and computing power must be deeply integrated with business use cases.

As a result, Xinqiao’s AI data center solutions cover the full lifecycle, from early planning and design to platform deployment and later operations and maintenance. They can closely fit government procurement processes and domestic compliance requirements, avoiding the traditional “equipment delivery means the end” model.

To meet demand for scaled AI deployment across industries, Xinqiao continues to build general-purpose computing power support capabilities for multiple scenarios, with a focus on manufacturing, healthcare, education, finance and government services:

In manufacturing, it supports intelligent perception, quality management and production process optimization, helping industrial systems move toward greater intelligence and precision. Through standardized computing power products and composable deployment plans, it helps customers lower the barrier to implementing AI applications and accelerates the shift from isolated use cases to scaled, routine operations;

In healthcare, it can support imaging analysis, assisted diagnosis and the intelligent use of medical data, helping improve the efficiency and quality of medical services;

In education, its capabilities can support intelligent teaching, personalized learning and content generation, advancing the digitalization and broader accessibility of education resources;

In finance, it provides stable and sustainable intelligent support for scenarios such as intelligent customer service, risk identification, business analysis and intelligent decision-making;

In government services, it supports automated office work, intelligent upgrades to public services and stronger data governance capabilities, improving the responsiveness of public services.

Through application adaptation and continuous optimization across industries, Xinqiao Semiconductor is helping customers improve computing power utilization and reduce total cost of ownership, pushing Chinese computing power into real business systems and creating a value loop from computing power investment to commercial monetization.

Going forward, Xinqiao will continue to promote the coordinated development of next-generation AI chips and AI data center platforms, working with government and enterprise customers, carriers and industry partners to build an open, collaborative and mutually beneficial domestic computing power ecosystem, and to move computing power from “usable” to “easy to use.”

Amid the AI computing power wave, Xinqiao, as a startup, is using a pragmatic approach to innovation to explore efficient adaptation paths for Chinese AI chips, from underlying architecture to scenario-based applications.

Only when computing power becomes truly “plug and play” can the inclusive value of AI technology be fully released, empowering industries across the economy to move into a new stage of intelligence.