March 24, 2025

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Ant Group Cuts AI Training Costs 20% with Chinese-Made Semiconductors

content="Recent advancements in artificial intelligence have led to a significant increase in AI development, with companies around the world investing heavily in the technology. The US and China are at the forefront of this race, with each country trying to outdo the other in terms of innovation and progress. In a major breakthrough, Ant Group, a Chinese fintech company, has developed a method to reduce AI training costs by 20% using Chinese-made semiconductors. Jack Ma Muscles Into the US-China AI Race Ant Group has developed techniques for training AI models with Nvidia alternatives, potentially lowering costs by 20%. The company is still using Nvidia for AI development but is now relying mostly on tech from other companies, including AMD, Alibaba, and Huawei, for its latest models. Ant published a research paper this month that claimed its models at times outperformed Meta in certain benchmarks. If they work as advertised, Ant's platforms could mark another step forward for Chinese AI development. The development marks Ant's entry into a race between Chinese and US companies that's accelerated since the billions invested by OpenAI and Google. Ant's models have yielded results similar to those produced with chips such as the H800. Jack Ma-backed Group Cuts AI Training Costs 20% Ant Group, the fintech giant, has made a major breakthrough in AI model training by cutting training costs by 20% with Chinese-made semiconductors. The innovative method was developed with chips from Alibaba and Huawei. The new technique builds on the Mixture of Experts machine learning method, which breaks down tasks into smaller data sets for efficient processing. Ant Group has claimed that its AI models, built on Chinese semiconductors, have yielded results similar to those produced with chips such as the H800. The company has disclosed that training one trillion tokens cost around 6.35 million yuan on high-performance hardware, but its optimized method could bring this down to 5.1 million yuan by utilizing lower-specification hardware. Ant Group Turns to Alibaba and Huawei Chips as Viable Nvidia Alternatives for AI Training Ant Group has found domestic alternatives to Nvidia's leading semiconductors for AI development. The company has joined other China-based firms looking to replicate the success of DeepSeek. While many are looking to cut the costs of AI development, some executives have predicted that much more money will be needed. Ant Group is using the newly acquired chips to develop techniques for training AI models, such as the Mixture of Experts approach. The domestic chips provided the same results as Nvidia's H800 chips, which are the usual semiconductors the company relies on. Companies like Nvidia have created modified versions of their advanced AI chips specifically for the Chinese market. Ant Group Reduces AI Training Costs by 20% Using Made-in-China Chips Ant Group has achieved an important advancement in artificial intelligence model training by using Chinese-made semiconductors. The company has developed a method that reduces AI training costs by around 20% by incorporating chips from Alibaba Group and Huawei Technologies. Despite using locally produced chips instead of relying on costly, high-end imported technology and hardware, the Chinese company is still capable of delivering high-performance results and remains competitive. Ant Group's models have outperformed those from larger international tech companies in certain benchmarks. The company has reported that training an AI model on one trillion tokens typically costs around 6.35 million yuan when using high-performance hardware, but its optimized method could bring this down to about 5.1 million yuan. Ant Group Upgrades AI for Healthcare Services Ant Group has upgraded its AI for healthcare services, using technologies like DeepSeek R1/V3, Alibaba's Qwen, and Ant Group's BaiLing. The healthcare AI model is built on these models and is able to answer questions about medical topics, and can also help improve patient services. The company announced 'major upgrades' to its AI solutions for healthcare, which it said were being used by seven major hospitals and healthcare institutions in Beijing, Shanghai, Hangzhou, and Ningbo. Ant Group Leverages Domestic Chips to Slash AI Training Expenses Ant Group has reportedly turned to Chinese-made semiconductors to cut AI training costs by 20%. Utilizing chips from Alibaba Group and Huawei Technologies, the firm developed models using the Mixture of Experts approach, matching Nvidia Corp.'s H800 chip capabilities. While still employing chips from Nvidia for some AI activities, the Jack Ma-backed company is increasingly favoring alternatives like Advanced Micro Devices and local chips for its latest models. This transition aligns with the broader race between Chinese and U.S. firms in AI innovation, intensified by methods that rival the costly investment seen by OpenAI and Google's Alphabet Inc. Alibaba-Affiliate Ant Combines Chinese and U.S. Chips to Slash AI Development Costs Alibaba-affiliate Ant Group is using both Chinese and U.S.-made semiconductors for building more efficient artificial intelligence models. The combination of chips not only reduces the time and cost of training AI models but also limits reliance on a single supplier such as Nvidia. The company announced 'major upgrades' to its AI solutions for healthcare, which it said were being used by seven major hospitals and healthcare institutions. Ant operates Alipay, one of the two major apps for mobile payments in China, and has used chips from Alibaba and Huawei for training AI models. Ant Group Develops AI Models Using Chinese-Made Chips Ant Group has developed AI models using Chinese-made chips from firms like Alibaba and Huawei, reducing training costs by around 20%. The company used a Mixture of Experts approach, achieving performance close to Nvidia's restricted H800 chips. While Ant still uses some Nvidia and AMD hardware, it is increasingly turning to domestic alternatives. This shift reflects China's broader effort to build AI capabilities with local hardware in response to U.S. export controls. Ant claims its models have even outperformed Meta's in certain benchmarks, though these results have not been independently verified. Key Takeaways Ant Group has developed a method to reduce AI training costs by 20% using Chinese-made semiconductors. The company is still using Nvidia for AI development but is now relying mostly on tech from other companies, including AMD, Alibaba, and Huawei, for its latest models. Ant Group's models have yielded results similar to those produced with chips such as the H800. The company has disclosed that training one trillion tokens cost around 6.35 million yuan on high-performance hardware, but its optimized method could bring this down to 5.1 million yuan. Ant Group's models have outperformed those from larger international tech companies in certain benchmarks. The company has announced 'major upgrades' to its AI solutions for healthcare, which it said were being used by seven major hospitals and healthcare institutions. Ant Group is increasingly favoring alternatives like Advanced Micro Devices and local chips for its latest models. The company claims its models have even outperformed Meta's in certain benchmarks, though these results have not been independently verified. Ant Group has developed AI models using Chinese-made chips from firms like Alibaba and Huawei, reducing training costs by around 20%. The company used a Mixture of Experts approach, achieving performance close to Nvidia's restricted H800 chips. Ant Group is using both Chinese and U.S.-made semiconductors for building more efficient artificial intelligence models. The combination of chips not only reduces the time and cost of training AI models but also limits reliance on a single supplier such as Nvidia. "

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Artificial Intelligence AI Development Chinese AI US-China AI Race Ant Group AI Training Costs