China's attempts to dominate the world of artificial intelligence may be paying off, with industry insiders and tech analysts telling CNBC that Chinese AI models are already very popular and they are keeping pace with — and even surpassing — those from the United States in terms of performance.

AI has become the latest battle between the US and China, with both sides viewing it as a strategic technology. Washington continues to restrict China's access for advanced chips designed to help power artificial intelligence amid fears the technology could threaten US national security.

It led China to pursue its own approach to boosting the appeal and performance of its AI models, including relying on open-sourcing technology and developing its own super-fast software and chips .

Like some of the leading US firms in the space, Chinese AI firms are developing so-called large language models, or LLMs, which are trained on large amounts of data and support applications such as chatbots.

Unlike OpenAI's models that power the wildly popular ChatGPT, however, most of these Chinese companies are develop open-source, or open-weight, LLMs that developers can download and build on for free and without strict licensing requirements from the inventor.

On Hugging Face, a repository of LLMs, Chinese LLMs are the most downloaded, according to Tiezhen Wang, a machine learning engineer at the company. Qwen, a family of AI models created by a Chinese e-commerce giant Alibabais the most popular on Hugging Face, he said.

"Qwen is rapidly gaining popularity due to its excellent performance on competitive benchmarks," Wang told CNBC by email.

He added that Qwen has a "very favorable licensing model" which means it can be used by companies without the need for "extensive legal reviews."

Qwen comes in various sizes, or parameters, as they are known in the world of LLMs. Large parameter models are more powerful but have higher computational costs, while smaller ones are cheaper to run.

"Regardless of the size you choose, Qwen is likely to be one of the best performing models available right now," added Wang.

DeepSeek, a start-up, also made waves recently with a model called the DeepSeek-R1. DeepSeek said last month that its R1 model competes with OpenAI's o1 — a model designed to reason or solve more complex tasks.

These companies claim that their models can compete with other open source offerings such as When's Llama, as well as closed LLMs like those from OpenAI, in various functions.

"In the last year, we have seen the rise of Chinese open source contributions to AI with really strong performance, low cost to serve and high throughput," Grace Isford, partner at Lux Capital, told CNBC by email.

Open sourcing technology serves a number of purposes, including driving innovation as more developers have access to it, as well as building a community around a product.

It is not only Chinese firms that have launched open-source LLMs. Facebook parent Meta, as well as European start-up Mistral, also have open-source versions of AI models.

But with the technology industry caught in the geopolitical battle between Washington and Beijing, open-source LLMs give Chinese firms another advantage: they allow their models to be used globally.

"Chinese companies would like to see their models used outside of China, so this is definitely a way for companies to become global players in the AI ​​space," Paul Triolo, a partner at the firm, told CNBC by email. global consultancy DGA Group.

While the focus is on AI models at the moment, there is also debate about what applications will be built on them - and who will dominate this global internet landscape going forward.

"If you assume these basic frontier AI models are table stakes, it's about what these models are used for, like accelerating frontier science and engineering technology," Lux's Isford said. Capital.

Today's AI models have been compared to operating systems, such as Microsoft Windows, Google's Android and Apple's iOS, with the potential to dominate a market, as these companies do on mobile and PCs.

If true, this makes the stakes for building a dominant LLM higher.

"They (Chinese companies) perceive LLMs as the center of future technological ecosystems," Xin Sun, a senior lecturer in Chinese and East Asian business at King's College London, told CNBC by email.

"Their future business models will depend on developers joining their ecosystems, developing new applications based on LLMs, and attracting users and data from which profits can subsequently be generated through various means, including but very beyond directing users to use their cloud services," Sun added.

AI models are trained on vast amounts of data, which require large amounts of computing power. Currently, Nvidia is the main designer of the chips needed for this, known as graphics processing units (GPUs).

Many of the major AI companies are training their systems on Nvidia's most high-performance chips — but not in China.

Over the past year or so, the United States has increased export restrictions on advanced semiconductor and chipmaking equipment to China. This means NvidiaThe very front chips cannot be exported to the country and the company had to create semiconductors compliant with the sanctions to export.

Despite, these restraints, however, Chinese firms still managed to launch advanced models of AI.

"Major Chinese technology platforms currently have sufficient access to computing power to continue to improve models. This is because they have stockpiled large numbers of Nvidia GPUs and are also leveraging domestic GPUs from Huawei and other brands," said Triolo of the DGA Group.

Indeed, Chinese companies were boosting efforts to create viable alternatives to Nvidia. Huawei was one of the main players in the pursuit of this goal in China, while brands like Baidu and Alibaba were also investing in semiconductor design.

"However, the gap in terms of advanced hardware computing will become wider over time, particularly next year as Nvidia releases its Blackwell-based systems that are restricted for export to the China," said Triolo.

Lux Capital's Isford pointed out that China has been "systematically investing and growing their entire domestic AI infrastructure stack outside of Nvidia with high-performance AI chips from companies like Baidu."

"Whether or not Nvidia chips are banned in China will not prevent China from investing and building its own infrastructure to build and train AI models," she added.