Huawei is seeking to grab a bigger share of the Chinese market for artificial intelligence chips dominated by Nvidia, by helping local companies adopt their rival’s silicon for so-called “inference” tasks.

China’s leading AI companies rely on graphics processing units (GPUs) made by Nvidia to “train” large-scale language models, with the US chipmaker’s $3.4tn products seen as crucial to the development in technology.

Instead of challenging Nvidia to train, Huawei is positioning its latest Ascend AI processors as the hardware of choice for Chinese teams that run “inference”, the calculation that LLMs do to create a answer to a prompt.

The Chinese tech giant is betting that inference will become a bigger source of demand in the future when the pace of model training slows and AI applications like chatbots become more widespread.

“Training is important, but it only happens a few times,” said Georgios Zacharopoulos, a senior AI researcher who works on accelerating inference at Huawei’s Zurich lab. “Huawei is mostly focused on inference, which will ultimately serve more customers.”

It’s focused on the technically less challenging but potentially profitable path of retrofitting AI models trained on Nvidia products to run on Ascend chips, according to company employees and Ascend customers. Because Nvidia GPUs and Ascend operate on different softwareHuawei helps companies use a different software tool to make the two systems compatible.

Huawei’s push comes with top-down government support. Chinese officials have encouraged local tech giants to buy more of Huawei’s AI chips and switch from Nvidia.

A person familiar with Nvidia’s operations in China said Huawei was seen internally as the country’s most serious competitor, adding to its “advanced” chip design capabilities.

Washington has sought to curb Beijing’s AI development with export controls aimed at preventing the development of sensitive Chinese technologies.

Unlike their US rivals such as OpenAI and Google, the companies do not have access to the latest GPUs in China. But even if the Chinese teams only get Nvidia’s minimal H20 chips tailored to meet export controls, the less powerful GPUs remain in high demand because they are considered better than local alternatives.

Analyst and Huawei researchers Ascend is not yet ready to replace Nvidia for model training due to technical issues, such as the breakdown of the ways the chips interact with each other within a wider “cluster” of AI chips when training larger models.

“While Ascend chips perform well on a per-chip basis, there is a bottleneck in inter-chip connectivity,” said Lin Qingyuan, Bernstein’s China semiconductor analyst. “When training a large model, you have to divide it into small tasks. If one chip fails, the software has to find a way so that other chips can replace it without delay.”

Another challenge for Huawei is to convince developers to move from Nvidia’s Cuda software, known as the company’s “secret sauce” because it is easy for developers to use and can speed up data processing.

But Huawei’s soon-to-be-released updated version of its AI chip, the Ascend 910C, is also expected to address these concerns. “We expect this new generation of hardware to come with improved software that makes it more accessible for developers,” said a Huawei employee, who declined to be named.

Huawei and Nvidia are facing tough competition. Chinese internet group Baidu and chip designer Cambricon have taken steps to develop an AI chip. Meanwhile, in the US, Amazon and Microsoft are also betting that they can capture a large share of the market for chips for inference as AI applications become more widespread.

Estimates from SemiAnalysis, a chip consultancy, suggest that Nvidia made $12bn in sales in China last year by delivering 1mn of its H20 chips to the country, selling twice as many AI Chips as of Huawei with the Ascend 910B.

“Nvidia’s China-specific H20 GPUs make up the majority of AI chips sold in China. But the lead is quickly shrinking as Huawei increases manufacturing capacity,” said Dylan Patel, chief analyst at SemiAnalysis.

Industry insiders have warned that Huawei’s AI chip push is also being held back by insufficient supply, with two prospective customers telling the Financial Times they cannot get the chips.

Huawei did not respond to a request for comment. Nvidia declined to comment.

Analysts say Huawei’s manufacturing is likely to face challenges due to US export controls that have left Chinese craftsmen reliant on outdated chip-making equipment.

The focus of the inference also points to an emerging dynamic in Chinese AI that differs from the US. Washington’s export controls mean China’s AI players are not joining the same race as Silicon Valley rivals Meta, Elon Musk’s x.AI and OpenAI to build large mega-clusters in the most advanced Nvidia GPUs.

“Chinese companies play a different game. They pay more attention to inference than in the US because it is possible to make big gains in efficiency even with less powerful chips, which also means faster they will achieve commercialization,” said Bernstein analyst Lin.

Chinese companies are betting that they can stay competitive in AI by lowering the cost of inference, which in turn makes it cheaper to run AI applications, he said.

Last month, Hangzhou and Beijing-based start-up DeepSeek released its V3 model, which gained attention for its low training and inference costs compared to comparative models in the US.

The company proposed a new way for an AI model to selectively focus on specific parts of the input data as a way of reducing the costs of running the model. It also uses the “Mixture of Experts” technique that is popular with other Chinese AI beginningswhich also helps speed up inference as only part of the model is used to generate an answer.

DeepSeek said that Huawei has successfully adapted V3 to Ascend, providing detailed instructions for developers on how to use the chip. The FT used to be reported that Huawei is sending engineers to help customers migrate from Nvidia to Ascend.

Additional reporting by Zijing Wu in Hong Kong