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DeepSeek Huawei team up on AI chip software

Chinese artificial intelligence company DeepSeek has partnered with Huawei Technologies to develop programming tools for Huawei’s Ascend AI chips, marking a fresh step in China’s push to build a stronger domestic AI technology ecosystem.

The partnership focuses on the software needed to make AI chips easier and more efficient to use. DeepSeek has released open-source programming infrastructure for Huawei’s Ascend platform, covering tools designed to support computation and communication between chips.

The move is significant because advanced AI hardware needs a strong software ecosystem to reach its full potential. Nvidia has built a major advantage through its CUDA software platform, which developers widely use to program and optimise AI workloads on Nvidia GPUs. DeepSeek and Huawei are now working on alternatives designed specifically for Chinese AI processors.

A key part of the collaboration is TileLang, an open-source programming language developed to simplify the process of programming AI chips. DeepSeek says the language allows developers to work at a higher level while still accessing the performance of the underlying hardware.

The goal is to make it easier to develop and optimise AI applications without relying heavily on Nvidia’s software ecosystem. DeepSeek has described the development of such programming infrastructure as an important step towards creating a more independent AI computing ecosystem.

The companies have also worked together on a computing system built around 128 Huawei Ascend 950 chips. Known as a “supernode”, the system is designed to allow a large number of AI processors to work together, improving computing and communication between the chips.

Huawei provided support for the programming infrastructure used by the system, according to DeepSeek. The development comes shortly after Huawei unveiled its next-generation AI processors and supernode systems, highlighting the company’s growing focus on large-scale AI computing.

The partnership also builds on earlier cooperation between the two companies. DeepSeek has been working to adapt its AI models to Huawei hardware, including its V4 model, which supports Huawei’s Ascend platform.

That shift is important because AI models require much more than powerful chips. Developers also need programming languages, compilers, libraries and communication systems that allow processors to work together efficiently. A strong software layer can reduce the amount of time developers spend rewriting and optimising applications for different hardware platforms.

TileLang is aimed at addressing part of that challenge. By providing a common programming framework, DeepSeek hopes developers can more easily build applications for Huawei’s AI chips while maintaining greater control over how the hardware is used.

The development comes against the backdrop of growing competition between China and the United States over advanced semiconductor and AI technology. Restrictions on the export of some advanced US chips and technology to China have pushed Chinese companies to accelerate the development of domestic alternatives.

Huawei has emerged as one of the key players in that effort, particularly through its Ascend AI chip range. DeepSeek’s involvement adds the expertise of one of China’s most closely watched AI companies to the software side of Huawei’s semiconductor strategy.

Open-source development could also help the new ecosystem attract more developers. Giving programmers access to the underlying tools allows them to experiment, adapt the software and contribute improvements. A larger developer community could eventually help expand the number of applications that can run efficiently on Huawei hardware.

Still, building a credible alternative to Nvidia’s established ecosystem will take more than releasing new software. Developers will look at performance, reliability, compatibility, documentation and hardware availability before moving large AI workloads to a new platform.

The 128-chip Ascend 950 supernode is an important technical development, but its chip count alone does not establish how it compares with Nvidia-based systems. Meaningful comparisons would require independent testing under similar workloads, hardware configurations and software conditions.

The DeepSeek-Huawei partnership therefore represents a broader shift in China’s AI strategy. The focus is moving beyond simply producing domestic AI chips towards building the software and infrastructure needed to make those chips competitive and practical at scale.

DeepSeek brings experience in developing and optimising large AI models, while Huawei brings its Ascend processors and computing infrastructure. Their collaboration aims to connect those two strengths through a stronger software layer.

The bigger challenge is reducing dependence on established foreign technologies while giving developers a practical alternative. Success will depend on how quickly the tools mature and how widely they are adopted by China’s growing AI industry.

China’s AI chip race is consequently becoming a race over software as much as hardware. Powerful processors need efficient programming tools, and DeepSeek and Huawei are betting that an open-source ecosystem can help close that gap.

The latest partnership could give Chinese developers another route to build and run AI systems using domestic technology, while adding momentum to Huawei’s wider effort to develop an alternative AI computing ecosystem.

 

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Technology

Huawei accelerates AI chip push to challenge Nvidia

Huawei is moving faster in the artificial intelligence chip race, bringing forward the launch of its next-generation processors as China works to build a stronger domestic alternative to Nvidia.

The Chinese technology giant said it will launch two new AI chips in 2027. The Ascend 960DT is expected in the first quarter, while the Ascend 960PR will follow in the third quarter. The announcement was made at Huawei’s annual Connect conference in Shanghai on September 17.

The new timetable is earlier than Huawei had previously indicated. The company had earlier planned to release the Ascend 960 later in 2027. Splitting the product into two versions also reflects the different demands of AI workloads, including training large AI models and running AI applications after they have been developed.

Huawei’s move comes as demand for AI computing in China continues to grow. Eric Xu, one of the company’s rotating chairmen, said Huawei currently does not have enough production capacity to meet demand inside China. That shortage is also limiting the company’s ability to expand its AI hardware business overseas.

The situation highlights how important AI chips have become to China’s technology industry.

Powerful processors are needed to train and operate advanced AI models. Nvidia has built a dominant position in this market through its high-performance chips and CUDA software platform, which is widely used by AI developers.

Huawei is trying to build an alternative.

Its Ascend series has become one of the most important Chinese alternatives to Nvidia’s AI processors. US restrictions on the export of advanced semiconductors and chipmaking technology to China have added urgency to that effort.

Huawei executives say the company is gaining ground in the Chinese AI chip market. Xu has claimed that Ascend has a larger share of the domestic market than Nvidia, although Huawei did not provide figures to support the claim. Nvidia, meanwhile, continues to have a significant advantage in AI software and developer support.

Huawei is also taking a different approach to improving computing power.

Instead of relying only on making a single chip more powerful, the company is working on technologies that allow large numbers of processors to operate together. Its UnifiedBus technology is designed to connect processors with memory, storage and networking components so they can function as part of a much larger computing system.

The company has developed 11 semiconductors using the technology and says its systems can eventually connect up to one million AI processors. Huawei has already shipped more than 1,000 such AI computing systems to more than 370 customers.

This approach is becoming increasingly important as AI models grow more complex. Training a large model can require thousands of processors working simultaneously. Connecting chips into clusters can therefore increase overall computing capacity even when an individual processor cannot match the performance of the most advanced Nvidia chips.

Huawei has unveiled the Atlas 960 SuperPoD as part of this strategy. The company is developing larger AI computing systems that combine its processors, networking technology and other hardware into a single platform.

The company has also laid out a longer-term roadmap. Huawei plans further generations of Ascend processors, including the Ascend 970 in 2028 and Ascend 980 in 2029. It has said future generations will continue to deliver substantial increases in computing performance.

The rapid development comes despite significant challenges.

US export controls have restricted Chinese companies’ access to some advanced AI chips and semiconductor manufacturing equipment. Huawei has also faced limitations in obtaining the most sophisticated chipmaking technology, making it harder to compete directly with the latest processors produced by companies such as Nvidia.

That has pushed Huawei to focus on efficiency, chip design, networking and large-scale systems rather than competing on individual chip performance alone.

Software is another important part of the competition. Nvidia’s CUDA platform has become deeply embedded in AI development, giving the US company a large ecosystem of developers and applications. Huawei is working to expand its own software ecosystem and attract Chinese AI developers to its Ascend platform.

The company says more than 40 AI models have already been trained using its systems, while its developer community continues to expand.

China’s push for AI self-reliance is giving Huawei an important domestic market. Chinese technology companies are increasingly looking for locally developed chips and computing systems as US-China technology restrictions reshape the semiconductor industry.

The competition, however, is no longer simply about who makes the fastest AI chip. It is becoming a broader contest involving processors, software, networking, memory, data centres and the ability to connect thousands of chips into a single AI computing platform.

Huawei’s accelerated 2027 roadmap shows how quickly that contest is developing. The company is preparing to release new AI chips almost every year while building the infrastructure needed to support increasingly demanding AI applications.

Whether Huawei can close the remaining technology and software gap with Nvidia will depend on its ability to improve chip performance, expand production and strengthen its developer ecosystem.

But one thing is becoming clear: China’s AI ambitions are creating a rapidly expanding market for domestic AI chips, and Huawei intends to play a central role in it.

 

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Corporate

Huawei reveals new strategy for advanced chips

Huawei has introduced a new approach to developing advanced semiconductor chips, signalling its efforts to overcome challenges created by continuing US sanctions and restrictions on access to cutting-edge technology.

The company has proposed what it describes as a new “scaling law” for chip development, aimed at improving performance through different design methods rather than relying only on traditional techniques used in semiconductor manufacturing. The move comes as technology companies worldwide seek ways to build more powerful chips to support artificial intelligence, data processing and next-generation computing systems.

For years, the semiconductor industry has focused on making chips smaller and fitting more transistors onto them to increase speed and efficiency. However, as manufacturing becomes more complex and expensive, companies are increasingly exploring alternative methods to improve performance.

Huawei’s latest proposal reportedly focuses on restructuring how chips are designed and connected internally. Rather than depending solely on more advanced manufacturing processes, the company is looking at ways to improve computing capabilities through different architectures and system-level designs.

The announcement is being closely watched because Huawei has faced major restrictions from the United States in recent years, limiting its access to advanced semiconductor technology and manufacturing tools. These restrictions significantly affected the company’s smartphone and technology businesses and pushed it to accelerate efforts toward self-reliance.

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