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.
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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 per cent increase in model inference speed while reducing GPU usage by 50 per cent compared to foreign open-source frameworks, the company said.
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Does the arrival of China’s low-cost DeepSeek mean the end of Nvidia’s chip dominance?
Does the arrival of China’s low-cost DeepSeek mean the end of Nvidia’s chip dominance?
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.