DeepSeek V4 points to growing use of Huawei chips in AI models

• 
  
  DeepSeek’s V4 AI model may run on Huawei chips.
  
  


• 
  
  The move reflects a shift to domestic AI chips and software in China.
  
  

China’s push to reduce reliance on US technology is showing up in AI infrastructure.


A recent report by



The Information



, cited by



Reuters



, said that DeepSeek’s upcoming V4 model may run on Huawei chips rather than


the


NVIDIA hardware


that


still powers most large AI systems today.


The shift points to a broader change in AI infrastructure.

According to the report, DeepSeek has been adapting parts of its model to work with Huawei’s Ascend chips. At the same time, large Chinese firms such as Alibaba, ByteDance, and Tencent have placed orders for hundreds of thousands of Huawei chips ahead of the V4 release,


according to



Reuters



. The scale of those orders suggests a wider shift in infrastructure planning.

A move away from NVIDIA dominance

For years, companies building large AI models have


depended


on


GPUs from



NVIDIA



.


Its CUDA software stack and hardware, like the A100 and H100 chips, have set the standard for training models.

DeepSeek


appears to be


taking a different route.



Reuters



reported that DeepSeek withheld early access to V4 from US chipmakers such as AMD and NVIDIA, while


giving


Chinese suppliers such as Huawei more time to tune their software.


Models built for one chip type do not always run well on another. DeepSeek is said to be rewriting parts of V4’s code so the model can run on Huawei’s chips.

How V4 may compare to current frontier models

DeepSeek has already drawn attention with earlier models such as V3 and R1.



Reuters



has reported that DeepSeek claimed it built earlier models at a lower cost than many US rivals. Details on V4 remain limited, but it is


being built


on domestic chips.

The key difference is how those results


are achieved


. US models often rely on large clusters of high-end GPUs, which are expensive and energy-intensive. DeepSeek’s approach focuses more on efficiency per unit of compute.

This


does not mean Huawei chips match NVIDIA’s best hardware.



Reuters



reported in 2025 that Huawei and other Chinese chipmakers had struggled for years to match NVIDIA’s top-end chips for training models. Performance in real-world AI systems depends on hardware, software, and data. By adjusting the model to the hardware, DeepSeek may be narrowing that gap.

Why Huawei chips are central to this shift

Huawei has been developing Ascend AI chips. These chips


are already used


in some data centres and AI workloads within China.


Export controls from the United States have limited access to advanced NVIDIA chips,


which has increased


demand for local


options


.

The reported surge in orders from companies


like


Alibaba, ByteDance, and Tencent shows that demand is not limited to


one


or two projects.


It reflects a move to secure supply chains and reduce reliance on foreign hardware.

Huawei’s role goes beyond hardware.



Reuters



reported that DeepSeek worked with Huawei and Cambricon as it rewrote parts of V4’s code.

A parallel AI stack is taking


shape

These changes suggest that two AI ecosystems may be forming. One


is centred


on US technology, with NVIDIA hardware and software at its core. The other is forming around Chinese companies, with Huawei chips and local software stacks.

DeepSeek’s V4 model may become a key test of how viable that second system is. If the model performs well, it could encourage more companies to follow the same path.

At the same time, this shift could affect how AI costs are structured.



Reuters



has linked DeepSeek’s earlier low-cost model claims to investor concerns about the high spending levels of some US AI firms.

What this means for the broader AI race

The race to build better AI models


is often framed


as a contest of model size or benchmark scores. Control over chips, software, and supply chains can shape what is possible and at what cost.

DeepSeek’s move to Huawei chips does not settle that race, but it adds a new dimension. It shows that high-level AI work


is no longer tied


to a single hardware path. Different regions may build their own stacks, each with its own trade-offs.

If V4 delivers strong results, it could mark a turning point. It would show that


competitive AI systems can be built


outside the NVIDIA ecosystem.

Want to learn more about AI and big data from industry leaders?



Check out



AI


& Big Data Expo



taking place in Amsterdam, California, and London. The comprehensive event is part of



TechEx



and


is co-located


with other leading technology events


, click



here



for more information.

AI News is powered by



TechForge Media



. Explore other upcoming enterprise technology events and webinars



here



.