China would love a domestic Nvidia rival — but that’s proving quite the challenge
The flags of China and the USA are being displayed on a smartphone, with an NVIDIA chip visible in the background.
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Chinese companies are ramping up efforts to produce a viable alternative to Nvidia’s chips that power artificial intelligence as Beijing continues its efforts to wean itself off American technology.
U.S. sanctions slapped on China over the past few years, along with Nvidia‘s dominance in the space, have provided big challenges for Bejing’s efforts, at least in the short term, analysts told CNBC.
Nvidia’s well-documented boom has been driven by large cloud computing players buying its server products which contain its graphics processing units, or GPUs. These chips are enabling companies, such as ChatGPT maker OpenAI, to train their huge AI models on massive amounts of data.
These AI models are fundamental to applications like chatbots and other emerging AI applications.
The U.S. government has restricted the export of Nvidia’s most advanced chips to China since 2022, with restrictions tightening last year.
Such semiconductors are key to China’s ambitions to become a leading AI player.
CNBC spoke to analysts who identified some of China’s leading contenders that are looking to challenge Nvidia, including technology giants Huawei, Alibaba and Baidu and startups such as Biren Technology and Enflame.
The overarching view is that they are lagging behind Nvidia at this point.
“These companies have made notable progress in developing AI chips tailored to specific applications (ASICs),” Wei Sun, a senior analyst at Counterpoint Research, told CNBC.
“However, competing with Nvidia still presents substantial challenges in technological gaps, especially in general-purpose GPU. Matching Nvidia in short-term is unlikely.”
China’s key challenges
Chinese firms have a “lack of technology expertise”, according to Sun, highlighting one of the challenges.
However, it’s the U.S. sanctions and their knock-on effects that pose the biggest roadblocks to China’s ambitions.
Some of China’s leading Nvidia challengers have been placed on the U.S. Entity List, a blacklist which restricts their access to American technology. Meanwhile, a number of U.S. curbs have restricted key AI-related semiconductors and machinery from being exported to China.
China’s GPU players all design chips and rely on a manufacturing company to produce their chips. For a while, this would have been Taiwan Semiconductor Manufacturing Co., or TSMC. But U.S. restrictions mean many of these firms cannot access the chips made by TSMC.
They therefore have to turn to SMIC, China’s biggest chipmaker, whose technology remains generations behind TSMC. Part of the reason why it’s lagging behind, is because Washington has restricted SMIC’s access to a key piece of machinery from Dutch firm ASML, which is required to manufacture the most advance chips.
Meanwhile, Huawei has been pushing development of more advanced chips for its smartphones and AI chips, which is taking up capacity at SMIC, according to Paul Triolo, a partner at consulting firm Albright Stonebridge.
“The key bottleneck will be domestic foundry leader SMIC, which will have a complex problem of dividing limited resources for its advanced node production between Huawei, which is taking up the lion’s share currently, the GPU startups, and many other Chinese design firms which have been or may be cutoff from using global foundry leader TSMC to manufacture their advanced designs,” Triolo told CNBC.
Nvidia is more than just GPUs
Nvidia has found success due to its advanced semiconductors, but also with its CUDA software platform that allows developers to create applications to run on the U.S. chipmaker’s hardware. This has led to the development of a so-called ecosystem around Nvidia’s products that others might find hard to replicate.
“This is the key, it is not just about the hardware, but about the overall ecosystem, tools for developers, and the ability to continue to evolve this ecosystem going forward as the technology advances,” Triolo said.
Huawei leading the pack
Triolo identified Huawei as one of the leaders in China with its Ascend series of data center processors.
The firm’s current generation of chip is called the Ascend 910B, and the company is gearing up to launch the Ascend 910C, which could be on par with Nvidia’s H100 product, according to a Wall Street Journal report in August.
In its annual report earlier this year, Nvidia explicitly identified Huawei, among other companies, as a competitor in areas such as chips, software for AI and networking products.
In the area of software and building a developer community, Huawei “holds lots of advantages,” Triolo said. But it faces similar challenges to the rest of the industry in trying to compete with Nvidia.
“The GPU software support ecosystem is much more entrenched around Nvidia and to a lesser degree AMD, and Huawei faces major challenges, both in producing sufficient quantities of advanced GPUs such as part of the Ascend 910C, and continuing to innovate and improve the performance of the hardware, given U.S. export controls that are limiting the ability of SMIC to produce advanced semiconductors,” Triolo said.
Chip IPOs ahead?
The challenges facing China’s Nvidia competitors have been evident over the past two years. In 2022, Biren Technology carried out a round of layoffs, followed by Moore Threads the year after, with both companies blaming U.S. sanctions.
But startups are still holding out hope, looking to raise money to fund their goals. Bloomberg reported last week that Enflame and Biren are both looking to go public to raise money.
“Biren and the other GPU startups are staffed with experienced industry personnel from Nvidia, AMD, and other leading western semiconductor companies, but they have the additional challenge of lacking the financial depth that Huawei has,” Triolo said.
“Hence both Biren and Enflame are seeking IPOs in Hong Kong, to raise funding for additional hiring and expansion.”
Nvidia CEO Jensen Huang says artificial intelligence is the “great equalizer” because it lets anyone program using everyday language.
Speaking at London Tech Week on Monday, Huang said that, historically, computing was hard and not available to everyone. “We had to learn programming languages. We had to architect it. We had to design these computers that are very complicated,” he said on stage alongside U.K. Prime Minister Kier Starmer.
“Now, all of a sudden … there’s a new programming language. This new programming language is called ‘human.'”
Conversational AI models were thrown into the spotlight in 2022 when OpenAI‘s ChatGPT exploded onto the scene. In February, the San Francisco-based tech company said it had 400 million weekly active users.
Users can ask chatbots, such as ChatGPT, Google’s Gemini or Microsoft’s Copilot, questions and they respond in a conversational way that feels more like talking to another human than an AI system.
Jensen Huang, co-founder and chief executive officer of Nvidia, at the London Tech Week exposition in London, UK, on Monday, June 9, 2025.
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CEO Huang, whose company engineers some of the world’s most advanced semiconductors and AI chips, highlighted that this technology can now be used in programming. He highlighted that very few people know how to use programming languages like C++ or Python, but “everybody … knows ‘human’.”
“The way you program a computer today, to ask the computer to do something for you, even write a program, generate images, write a poem — just ask it nicely,” he said. “And the thing that’s really, really quite amazing is the way you program an AI is like the way you program a person.”
He gave the example of simply asking a computer to write a poem to describe the keynote speech at the London Tech Week event.
“You say: You are an incredible poet … And I would like you to write a poem to describe today’s keynote. And without very much effort, this AI would help you generate such a wonderful poem,” he said.
“And when it answers … you could say: I feel like you could do even better. And it would go off and think about it, and it’ll come back and say, in fact, I I can do better, and it does do a better job.”
Huang’s comments come as a growing number of companies — such as Shopify, Duolingo and Fiverr — encourage their employees to incorporate AI into their work. Indeed, last week OpenAI announced that it has 3 million paying business users.
Huang regularly touts AI’s ability to help workers do their jobs more efficiently and has encouraged workers to embrace the technology as they look to make themselves valuable employees — especially given the horror stories around AI’s potential to replace jobs.
“This way of interacting with computers, I think, is something that almost anybody can do, and I would just encourage everybody to engage it,” Huang added on Monday. “Children are already doing that themselves naturally, and this is going to be transformative.
— CNBC’s Cheyenne DeVon and Ashton Jackson contributed to this report.
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LONDON — Britain’s financial services watchdog on Monday announced a new tie-up with U.S. chipmaker Nvidia to let banks safely experiment with artificial intelligence.
The Financial Conduct Authority said it will launch a so-called Supercharged Sandbox that will “give firms access to better data, technical expertise and regulatory support to speed up innovation.”
Starting from October, financial services institutions in the U.K. will be allowed to experiment with AI using Nvidia’s accelerated computing and AI Enterprise Software products, the watchdog said in a press release.
The initiative is designed for firms in the “discovery and experiment phase” with AI, the FCA noted, adding that a separate live testing service exists for firms further along in AI development.
“This collaboration will help those that want to test AI ideas but who lack the capabilities to do so,” Jessica Rusu, the FCA’s chief data, intelligence and information officer, said in a statement. “We’ll help firms harness AI to benefit our markets and consumers, while supporting economic growth.”
The FCA’s new sandbox addresses a key issue for banks, which have faced challenges shipping advanced new AI tools to their customers amid concerns over risks around privacy and fraud.
Large language models from the likes of OpenAI and Google send data back to overseas facilities — and privacy regulators have raised the alarm over how this information is stored and processed. There have meanwhile been several instances of malicious actors using generative AI to scam people.
Nvidia is behind the graphics processing units, or GPUs, used to train and run powerful AI models. The company’s CEO, Jensen Huang, is expected to give a keynote talk at a tech conference in London on Monday morning.
Last year, HSBC’s generative AI lead, Edward Achtner, told a London tech conference he sees “a lot of success theater” in finance when it comes to artificial intelligence — hinting that some financial services firms are touting advances in AI without tangible product innovations to show for it.
He added that, while banks like HSBC have used AI for many years, new generative AI tools like OpenAI’s ChatGPT come with their own unique compliance risks.
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