Alibaba Unveils Chip, Plans 10-Trillion-Parameter Model
34 sourcesUpdated Sep 22, 2026
On Sept. 22, 2026, at the Apsara conference in Hangzhou, Alibaba CEO Eddie Wu unveiled the Zhenwu V900, calling it the "most powerful AI chip in China today." The company said the chip has three times the performance of the Zhenwu M890, can be clustered in groups of up to 500,000 chips, and is slated for commercial release in 2027. Alibaba said it is developing a Qwen model with 5 to 10 trillion parameters, versus 2.4 trillion in Qwen3.8-Max; Moonshot's Kimi K3 stands at 2.8 trillion. It plans over 20 gigawatts of data-center capacity by 2032. Hong Kong-listed shares rose about 5%. Wu said Alibaba is "mobilizing every resource" and that shortages "are currently limiting the speed at which we can scale our compute infrastructure." He said "machine intelligence today is not a substitute for human intelligence," predicted machines will eventually produce over 1,000 times more "thinking" than all of humanity (up from less than 3%), and stated "The truly groundbreaking products of the Machine Intelligence era have not yet arrived." Neil Shah said "Using extra computing power to make up for chip limits helps China stay strong locally"; Parv Sharma cited chip-foundry advances as another factor in any U.S.-China gap. CONTESTED: none found on core claims. One source specifies V900 mass production in Q1 2027 rather than 2027 generally. The news preceded Xi Jinping's expected Wednesday arrival in Washington to meet Donald Trump, after Huawei's chip unveilings the prior week.
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Center· 2 sources
“Alibaba Details New AI Chip, Sets Out Expansion Plans for Flagship Large Language Model”Right· 4 sources
The 5 percent stock jump shows investors see real value in pairing new hardware with bigger models, even if results are years away.
A 10 trillion parameter Qwen model would be enormous if they pull it off, though training costs and data needs could slow things down more than expected.
Alibaba claiming the Zhenwu V900 is China's top AI chip now is bold, but it still has to prove itself against global competition in real workloads.
