Chinese Open-Source AI Framework Chitu Challenges NVIDIA's Dominance in AI Chip Market

A New Chinese Open Source Framework Aims to Challenge Dependence on NVIDIA's Chips on AI Models

NVIDIA leads the AI chip market. However, due to U.S. hardware restrictions on China and the rise of non-NVIDIA GPUs, some businesses may seek to lessen their reliance on NVIDIA products. A team associated with China's Tsinghua University is joining the effort by releasing a new open source artificial intelligence (AI) framework, Chitu, made available under the Apache-2.0 license. Chitu is a high-performance inference framework for large language models, focusing on efficiency, flexibility, and availability. With its initial release, it supports various mainstream large language models, including DeepSeek, LLama series, Mixtral, and more. The report by South China Morning Post states that the framework can operate on chips made in China, challenging the supremacy of NVIDIA's Hopper series graphics processing units (GPUs). The information is referenced from a joint statement on Friday by the startup Qingcheng.AI and a team led by Zhai Jidong, computer science professor at Tsinghua University. The startup was founded in 2023 by Jidong, and his students from Tsinghua University, with him serving as chief scientist. The report states that it is backed by Beijing's municipal fund for the AI industry. The framework's GitHub page mentioned, "We not only focus on the popular NVIDIA GPUs, but pay special attention to all kinds of hardware environments, including legacy GPUs, non-NVIDIA GPUs and CPUs. We aim to provide a versatile framework to encounter the diverse deploying requirements." The report mentions that the company claims to have achieved a 315% increase in model inference speed while reducing GPU usage by 50% compared to foreign open source frameworks. This is as per the test with DeepSeek-R1 using NVIDIA's A800 GPUs. The team states that the framework is ready and deployed for real-world production.

Nvidia Faces New AI Challenge As Chinese Start-Up Unveils Framework To Cut Reliance On Its GPUs - Alibaba Gr Hldgs (NYSE:BABA), Baidu (NASDAQ:BIDU)

A new artificial intelligence framework developed by a Chinese start-up could reduce reliance on Nvidia Corp.'s NVDA chips for AI model inference, marking the latest effort by Chinese tech companies to achieve technological self-sufficiency amid U.S. export restrictions. What Happened: Qingcheng.AI, founded by Tsinghua University professor Zhai Jidong, unveiled "Chitu" - a high-performance inference framework for large language models that can operate on Chinese-made chips, reported South China Morning Post. The open-source framework directly challenges Nvidia's dominance in supporting advanced AI models like DeepSeek-R1, according to a joint statement released Friday. When tested with DeepSeek-R1 using Nvidia's A800 GPUs, Chitu achieved a 315% increase in model inference speed while reducing GPU usage by 50% compared to foreign frameworks, the company claimed. The development comes amid heightened AI competition in China following DeepSeek's breakthrough in January, which demonstrated high-performance models at significantly lower costs than U.S. competitors. DeepSeek's success triggered a selloff in U.S. tech stocks, with Nvidia losing $593 billion in market value as investors feared increased competition. See Also: Ross Gerber Shares 'Peaceful Display Of Distaste For Elon Musk' In Santa Monica, His 9-Year Old Observes, 'Glad We Don't Have A Tesla' Why It Matters: Chinese tech giants are rapidly entering the race. Baidu Inc. BIDU on Sunday unveiled ERNIE X1, claiming performance comparable to DeepSeek-R1 at half the price. Alibaba Group Holding Ltd. BABA recently launched R1-Omni, an emotion-reading AI model available for free. These initiatives reflect China's broader push for technological independence after Washington banned sales of Nvidia's advanced H100 and H800 chips to China-based clients. Backed by Beijing's municipal AI fund, Qingcheng.AI has partnered with top Chinese GPU manufacturers including Moore Threads, Enflame and Iluvatar CoreX. The AI surge has reignited investor interest in Chinese tech, potentially reversing three years of venture capital decline. "People are rushing just to find the next DeepSeek," said Annabelle Yu Long, founding partner of BAI Capital, as the Chinese government prepares a fund expected to mobilize 1 trillion yuan ($137.7 billion) for tech investment. Read Next: Trump Says He Was 'Little Bit Sarcastic' When He Said He Would End The Russia-Ukraine War In A Day: 'What I Really Mean Is...' Image Via Shutterstock Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. BABAAlibaba Group Holding Ltd$139.70-0.99%Stock Score Locked: Want to See it? Benzinga Rankings give you vital metrics on any stock - anytime. Reveal Full ScoreEdge RankingsMomentum96.64Growth65.09Quality67.08Value76.20Price TrendShortMediumLongOverviewBIDUBaidu Inc$94.490.71%NVDANVIDIA Corp$121.36-0.25%Market News and Data brought to you by Benzinga APIs

Chinese startup challenges Nvidia's AI lead with new chip framework

Visitors watch a Nvidia hologram at the stand of Dell Technologies, at the MWC (Mobile World Congress) in Barcelona, Spain, March 5. AFP-Yonhap A new artificial intelligence (AI) framework developed by teams associated with China's Tsinghua University is said to be able to reduce reliance on Nvidia chips for AI model inference, marking the latest effort by the country to enhance technological self-sufficiency. Chitu, a high-performance inference framework for large language models (LLMs), can operate on chips made in China, challenging the dominance of Nvidia's Hopper series graphics processing units (GPUs) in supporting certain models, such as DeepSeek-R1, according to a joint statement by start-up Qingcheng.AI and a team led by computer science professor Zhai Jidong at Tsinghua University on Friday. AI frameworks serve as the building blocks of sophisticated, intelligent AI models, offering a collection of libraries and tools that enable developers to design, train and validate complex models efficiently. The Chitu framework, which has been open-sourced since Friday, supports mainstream models, including those from DeepSeek and Meta Platforms' Llama series, according to the company. When tested with the full-strength version of DeepSeek-R1 using Nvidia's A800 GPUs, the framework achieved a 315 percent increase in model inference speed while reducing GPU usage by 50 percent compared to foreign open-source frameworks, the company said. The initiative is part of a broader effort by Chinese AI companies to lessen dependence on Nvidia, whose high-performance GPUs are subject to US export controls. Nvidia is banned by Washington from selling its advanced H100 and H800 chips from the Hopper series to China-based clients. The rise of Hangzhou-based DeepSeek, which has developed its AI models at a fraction of the cost and computational resources used by Western peers, has also raised questions about a potential decline in demand for Nvidia GPUs. Nvidia and DeepSeek logos are seen in this illustration taken, Jan. 27. Reuters-Yonhap Qingcheng.AI was founded in 2023 by Zhai and his students from Tsinghua University, with Zhai serving as chief scientist. Backed by Beijing's municipal fund for the AI industry, the start-up has partnered with top Chinese GPU manufacturers, including Moore Threads, Enflame and Iluvatar CoreX, according to CEO Tang Xiongchao in an interview with Chinese media last year. Other tech companies in China have also intensified their efforts to reduce reliance on foreign technology following the DeepSeek momentum. In February, Infinigence AI -- a computing infrastructure platform provider supported by talent from Tsinghua and funding from major Chinese tech firms -- announced it was working to foster collaboration among the country's seven leading AI chip developers: Biren Technology, Hygon Information Technology, Moore Threads, MetaX, Enflame, Iluvatar CoreX and Huawei Technologies' Ascend. In a recent research paper, scientists from ByteDance, the parent company of TikTok, reported a 170 percent increase in LLM training efficiency using an optimized system. The new system has already been implemented in some of ByteDance's production environments, achieving "savings of millions of GPU hours," the company said. Read the full story at SCMP.