Hua Hong Group has developed advanced chip manufacturing technology capable of producing processors at the 7-nanometre level, according to people familiar with the matter who spoke to Reuters.

The development marks an important step in China’s effort to build a domestic semiconductor ecosystem capable of supporting artificial intelligence and high-performance computing.

The technology is being developed by the group’s contract chipmaking arm, Huali Microelectronics, which is preparing a 7-nanometre (nm) manufacturing process at its facility in Shanghai, the sources said.

If the technology is successfully deployed at scale, Hua Hong would become the second Chinese semiconductor manufacturer capable of producing chips at the 7-nm node, joining Semiconductor Manufacturing International Corporation, or SMIC, the country’s largest contract chipmaker.

The development signals steady progress in Beijing’s attempt to build advanced semiconductor capabilities at home after years of U.S. export restrictions targeting China’s access to cutting-edge chip technologies.

The ability to manufacture chips at 7 nm represents a key technological threshold for modern computing systems. Chips produced at this node are widely used in artificial intelligence accelerators, advanced mobile processors, data center hardware, and high-performance computing systems.

Although global leaders have moved to even smaller manufacturing processes such as 5-nm and 3-nm, the 7-nm node remains highly relevant for AI workloads and advanced computing applications.

Achieving this capability domestically is strategically significant for China because it reduces dependence on overseas semiconductor foundries and strengthens the country’s ability to support its rapidly expanding AI industry.

People familiar with the project said Huawei Technologies has been working with Hua Hong on developing the 7-nm manufacturing technology. The collaboration underlines Huawei’s central role in China’s semiconductor self-sufficiency push after the company was cut off from many Western chip suppliers and manufacturing partners due to U.S. sanctions.

Huawei has since invested heavily in rebuilding a domestic semiconductor supply chain, partnering with chip designers, fabrication plants, and equipment manufacturers across China. Such collaborations have become increasingly important as Beijing attempts to build an integrated technology ecosystem capable of designing, manufacturing, and deploying advanced processors without relying heavily on foreign technology.

Test Production And Early Industry Adoption

Research and development work on the 7-nm process began last year at Hua Hong Fab 6, the company’s most advanced semiconductor plant located in Shanghai. Sources said the facility is expected to start with relatively modest output, producing a few thousand silicon wafers per month by the end of the year, with capacity expected to scale gradually as manufacturing processes are refined.

Chinese graphics processor developer Biren Technology has reportedly already used the new production line for a tape-out — the stage where a chip design is finalized and turned into a physical prototype before mass manufacturing.

The development is particularly significant for Biren, which lost access to overseas manufacturing services after being placed on a U.S. trade blacklist in 2023. That move forced the company to stop using fabrication services from Taiwan Semiconductor Manufacturing Company, the world’s largest contract chipmaker.

Access to domestic manufacturing capacity, therefore, provides Chinese chip designers with an alternative path to bring advanced processors to market.

The domestic equipment ecosystem is emerging, underpinning progress among China’s semiconductor equipment makers.

Sources said Hua Hong’s work on the 7-nm process involved support from domestic suppliers, including SiCarrier, a Huawei-backed semiconductor equipment company. SiCarrier reportedly tested its manufacturing equipment at a facility in Shenzhen last year as part of efforts to develop indigenous tools for advanced chip production.

The rise of domestic equipment manufacturers is a critical element of China’s semiconductor strategy, as export restrictions have limited access to some of the most advanced machinery used in chip fabrication.

The Challenge of Technology Constraints

China’s semiconductor industry continues to face major technological hurdles despite these advances. The most sophisticated lithography systems required for the world’s most advanced chips are produced by ASML in the Netherlands. These extreme ultraviolet (EUV) machines enable chipmakers to produce processors at cutting-edge nodes such as 5-nm and 3-nm.

Chinese companies do not currently have access to EUV technology due to export controls.

Instead, Chinese foundries have relied on older deep ultraviolet lithography equipment to produce advanced chips using complex multi-patterning techniques. While technically feasible, this method can significantly reduce production efficiency and chip yields.

Analysts have said SMIC has used such techniques to produce 7-nm chips, although yields — the proportion of usable chips produced from each wafer — remain relatively low. However, it remains unclear how Hua Hong achieved its 7-nm capability, what equipment was used, or how efficient the process will be at scale.

Financial Backing And Industrial Consolidation

The push into advanced chip manufacturing is backed by significant investment. In December, Hua Hong Semiconductor announced plans to acquire a controlling stake in Huali Microelectronics and raise 7.56 billion yuan ($1.10 billion) to support research, development, and technological upgrades at the foundry.

The move is part of a broader effort by Chinese semiconductor companies to consolidate resources and accelerate progress toward advanced manufacturing capabilities.

The Hua Hong Group currently operates seven semiconductor fabrication plants. Fab 6 — where the new 7-nm technology is being developed — is its most advanced facility and currently produces logic chips at the 22-nm and 28-nm nodes. Another plant, Fab 5, focuses on mature technologies between 40-nm and 55-nm, which are widely used in automotive electronics, industrial systems, and consumer devices.

Investors reacted strongly to the report of Hua Hong’s technological progress, highlighting its importance. Shares in Hua Hong Semiconductor surged about 12% following the news, reflecting optimism that China’s semiconductor industry may be closing part of the gap with global leaders.

The progress is also another example of how China’s chip sector has continued to advance despite restrictions imposed by the United States. Although Washington has eased some export controls in recent months — allowing companies such as Nvidia to sell certain AI chips to Chinese customers — Beijing has continued encouraging domestic companies to adopt homegrown semiconductor technologies.

Despite the breakthrough, China’s semiconductor industry still faces a long path to matching global leaders. Companies such as TSMC and Samsung produce chips at far smaller process nodes and at vastly larger volumes, supported by decades of technological experience and access to the world’s most advanced equipment.

However, the emergence of a second Chinese manufacturer capable of producing 7-nm chips suggests that China’s semiconductor ecosystem is gradually strengthening.

For Beijing, the strategic goal is not necessarily to surpass global leaders immediately, but to ensure that critical technologies — particularly those needed for artificial intelligence, telecommunications, and national security — can be produced domestically if geopolitical tensions disrupt global supply chains.

Nvidia on Monday unveiled a new generation of computing platforms designed for orbital data centers, marking a significant step toward deploying artificial intelligence infrastructure in space as demand for computing power continues to surge.

The announcement came during the company’s GTC 2026 conference, where CEO Jensen Huang described space-based computing as the next frontier for AI systems that increasingly require massive processing capacity close to where data is generated.

“Space computing, the final frontier, has arrived,” Huang said during the event. “As we deploy satellite constellations and explore deeper into space, intelligence must live wherever data is generated.”

The move marks a major shift as the AI industry explores unconventional solutions to meet the soaring demand for computing resources driven by generative AI, robotics, and autonomous systems.

A New Computing Platform Built For Space

At the center of the announcement is Nvidia’s Vera Rubin Space-1 Module, a computing platform designed specifically for use in satellites and orbital infrastructure. The module integrates Nvidia’s IGX Thor and Jetson Orin processors and is engineered to operate in size-, weight-, and power-constrained environments, conditions that are critical for space missions where hardware must be compact, energy-efficient, and resilient.

According to the company, the platform will support space missions being developed by several industry partners, including Axiom Space, Starcloud, and Planet Labs. These systems are expected to enable satellites to process data directly in orbit, reducing the need to transmit massive volumes of raw data back to Earth before analysis.

Such an approach could transform how Earth observation, communications, and deep-space exploration missions operate. Traditionally, satellites have collected data and transmitted it back to ground-based data centers for processing.

Nvidia’s approach aims to bring AI computing closer to the data source, allowing satellites to analyze information in real time. This capability could allow satellites to filter and process imagery, track weather systems, monitor infrastructure, or detect anomalies without waiting for instructions from Earth.

For example, Earth-observation satellites could use onboard AI to identify natural disasters, track deforestation, or analyze agricultural activity instantly, dramatically reducing response times. The development also aligns with a broader trend in computing known as edge AI, where processing occurs near the point where data is generated rather than in distant centralized servers.

The Engineering Challenges

Although the technology is promising, significant engineering hurdles remain before orbital data centers become widespread. One of the most difficult challenges is cooling high-performance computing systems in the vacuum of space.

“In space, there’s no convection, there’s just radiation,” Huang said during his keynote address.

“And so we have to figure out how to cool these systems out in space, but we’ve got lots of great engineers working on it.”

Cooling is a major issue because traditional data centers rely on air or liquid circulation to remove heat generated by processors. In space, heat must instead be dissipated through radiation, requiring new thermal designs and materials.

The Search For Power Beyond Earth

The push toward space-based computing is partly driven by the rapidly escalating energy demands of artificial intelligence. The construction of massive AI data centers on Earth has already been linked to rising electricity consumption and strain on power grids in several regions.

By contrast, satellites and orbital facilities could potentially harness virtually unlimited solar energy without the land and infrastructure constraints faced by terrestrial data centers. Technology companies are increasingly studying whether space could provide a long-term solution to the energy demands of large-scale computing.

In November, Google announced Project Suncatcher, an initiative exploring the feasibility of deploying computing infrastructure powered by solar energy in orbit.

The concept is also gaining traction among companies involved in space launch and satellite infrastructure. Last month, Elon Musk’s AI startup xAI was acquired by SpaceX in a deal valued at $1.25 trillion, a move widely interpreted as part of a strategy to build AI-powered computing systems in orbit.

SpaceX is one of Nvidia’s largest customers for AI chips, supplying hardware used to train and operate advanced AI models. Earlier this year, SpaceX also asked the Federal Communications Commission for approval to launch as many as one million satellites intended to support orbital AI infrastructure.

With generative AI models becoming larger and more computationally demanding, traditional data centers on Earth may struggle to keep pace with the scale of future workloads. Against this backdrop, space has become an alternative. But Space-based computing remains an ambitious concept with significant technical and regulatory challenges.