At the 2026 Hangzhou Apsara Conference (云栖大会) opening on September 22, Alibaba CEO Wu Yongming put it on the table: the next-generation Tongyi Qianwen (Qwen) model will sit between 5 and 10 trillion parameters, while the current flagship Qwen3.8 Max carries 2.4 trillion. That makes the upcoming model two to four times the size of today's flagship, and would put it among the largest model systems in the world.
This time, Alibaba is not just sketching a roadmap. Alongside the model plan, Pingtouge unveiled a new training-and-inference AI chip called Zhenwu V900. Wu called it "the most powerful AI chip in China today," delivering three times the compute of the prior Zhenwu M890, and a single AI cluster built on it can hold up to 500,000 accelerator cards. Mass production is locked in for Q1 2027. For context, M890 already handled inference for models above 2 trillion parameters — and Wu noted that only a handful of companies in the world can do this.
Recursive Self-Improvement (RSI): the model as its own coach
The more interesting move is recursive self-improvement (RSI). Wu showed how the Qwen team is experimenting with letting the model discover its own capability boundaries, design experiments, generate data, and iterate on its own. In other words, the model is no longer just a thing being trained — it is learning to coach itself. Alibaba frames this path as the infrastructure of higher-grade AI systems: if it works, the train-infer-iterate loop gets compressed inside the model.
5-10 trillion is just the middle stop
The numbers line up the same way. Qwen3.8 Max today is 2.4 trillion; Qwen 4, currently in training, will continue to scale up; and the planned Qwen 4.5 and Qwen 5 series are aimed squarely at the 5-10 trillion range. In other words, between today and the next flagship there is more than one rung, and each rung is several times the size of the current mainstream flagships.
The supporting compute stack is being pushed at the same time
The supporting compute base is just as aggressive. Alibaba also laid out a 2032 roadmap: global Alibaba Cloud data center capacity above 20 gigawatts, and Pingtouge's AI supernodes entering large-scale commercial operation starting this quarter. Wu's read on the market is that mid- and long-term AI compute demand is growing far faster than supply — meaning Alibaba is betting not just on one or two flagship models, but on pushing "ultra-large models + self-developed chips + data centers" to their limits simultaneously.
Why a three-piece bet now
This three-piece strategy does not sit in isolation. With US high-end chip export controls tightening layer by layer, Chinese tech companies have to push the model, the chip, and the infrastructure forward together. V900's 3x compute, the 500,000-card single cluster, and the 20GW data center target all point in the same direction: build the stack yourself in places where others cannot sell in. The signal from the 2026 Apsara Conference is that this stack is accelerating at Alibaba.
Can all three hit Q1 2027
At the industry level, what is most worth tracking from this announcement is not any single number, but that Alibaba has bound "model scaling" and "model self-evolution" into one main line. Pushing parameters to 5–10 trillion is a necessary condition; RSI is the software path that actually makes that parameter count usable; Zhenwu V900 is the hardware floor. If any one of these three breaks, the whole roadmap gets discounted. Whether the Qwen team can drive all three to the Q1 2027 mass-production node will be one of the progress bars worth watching most closely in China's large-model race over the next year.