During a recent event in Hangzhou, Alibaba Group's CEO Eddie Wu announced ambitious plans for the development of a new artificial intelligence model, aimed at reaching between 5 trillion and 10 trillion parameters. This initiative was part of a broader strategy that encompasses AI model development, semiconductor innovation, and the expansion of data center infrastructure.
At the Alibaba Cloud Apsara Conference, Wu emphasized that the Qwen research team is making strides in refining model architecture and optimizing data, with an eye towards tackling more complex tasks and pushing towards artificial superintelligence (ASI).
In a noteworthy update, Alibaba revealed that its forthcoming Qwen 4 model is currently in training, with the Qwen 4.5 and Qwen 5 series expected to scale up to the proposed 5 to 10 trillion parameters. For context, the existing flagship version, Qwen 3.8 Max, features 2.4 trillion parameters, which means the new models could be two to four times larger.
Wu highlighted the advanced capabilities of the M890 AI supernode, which already performs inference tasks for models exceeding 2 trillion parameters, a feat achieved by only a select few companies globally.
Additionally, Alibaba unveiled its Zhenwu V900 AI chip, a cutting-edge product from its T-Head semiconductor division, which Wu proclaimed as the most powerful AI chip in China. It boasts three times the performance of its predecessor, the M890, and a single cluster can support up to 500,000 cards for training and inference of advanced models. The mass production and commercial launch of the Zhenwu V900 are slated for the first quarter of 2027.
The announcement comes amid a race among Chinese companies to develop domestic alternatives to Nvidia's GPUs due to U.S. export restrictions. Wu also set an ambitious goal for Alibaba Cloud to expand its global data center capacity to over 20 gigawatts by 2032. Although he noted strong customer demand for AI, Wu acknowledged that global supply chain shortages are hindering quicker growth.
Wu characterized this moment as the beginning of a new "Machine Intelligence" era, similar to the significance of the Industrial Revolution. He forecasts that machines will ultimately achieve over 1,000 times the cognitive capacity of humanity, up from less than 3% today. He likened AI software development to early electrical inventions, suggesting that while significant advancements are underway, the truly transformative products of the Machine Intelligence era are yet to be realized.




