Alibaba Unveils Zhenwu V900 AI Chip, Plans 20GW Datacenter Expansion and 10 Trillion Parameter Models

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Alibaba CEO Eddie Wu unveiled the Zhenwu V900 at Apsara Conference 2026, calling it China's most powerful AI chip with three times the performance of its predecessor. The company plans to scale Alibaba Cloud to 20GW capacity by 2032 and train AI models reaching 5-10 trillion parameters, positioning itself against U.S. export controls.

Alibaba Debuts Zhenwu V900 as China's Most Powerful AI Chip

Alibaba CEO Eddie Wu introduced the Zhenwu V900 AI chip at the Apsara Conference 2026, declaring it China's most powerful AI chip with three times the performance of the previous-generation M890

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. Developed by Alibaba's T-Head semiconductor unit, the processor features 216GB of memory and 1,200GB/s of inter-chip bandwidth, representing substantial upgrades from the M890's 144GB memory and 800GB/s interconnect

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. The chip handles both high-precision model training and ultra-low-precision inference, supporting formats from FP32 down to FP4 natively

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. T-Head enhanced the Tensor Core arithmetic unit specifically for improved instruction precision in FP8 and FP4 formats, alongside richer scaling factor formats under MXFP8 and MXFP4

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. Mass production and commercial release are scheduled for the first quarter of 2027, accelerated from the original third-quarter timeline

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Source: The Register

Source: The Register

Scaling to 500,000-Chip Supercluster for Frontier Model Training

The Zhenwu V900 can scale to a supernode cluster comprising up to 500,000 cards, a dramatic increase from the M890's maximum configuration of 128 chips

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. T-Head states that more than 1,000 V900 chips can function as a single system for frontier model training and inference

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. However, Alibaba released limited technical specifications, omitting FLOPS figures, process node details, foundry information, and power consumption metrics

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. This contrasts with Huawei's competing Ascend 960PR, scheduled for third quarter 2027, which lists 192GB memory capacity, 2.4TB/s memory bandwidth, and a 2.2TB/s scale-up interconnect

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. As of May, T-Head had shipped more than 560,000 Zhenwu chips to over 400 external customers, a count Alibaba now places above 650 customers spanning industries from automotive to language models and embodied intelligence

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. Alibaba expects significant growth in annual AI chip shipments and plans to refresh the Zhenwu lineup annually, with a J900 model due in third quarter 2028

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AI Model with 5 Trillion to 10 Trillion Parameters on Roadmap

Alibaba is currently training Qwen 4 and has placed Qwen 4.5 and Qwen 5 on its roadmap, with both models targeting 5 trillion to 10 trillion parameters

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. This represents a substantial increase from the current Qwen 3.8-Max flagship model with 2.4 trillion parameters and surpasses Moonshot's Kimi K3 at 2.8 trillion parameters

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. Eddie Wu framed this scaling as a pathway to artificial superintelligence, with larger models targeting longer and more complex tasks

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. The Qwen team is exploring recursive self-improvement (RSI), a technology where models identify their own weaknesses, run experiments, and generate training data with minimal human involvement

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. Wu described the progress as meaningful, though details remain limited

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. Alibaba claims Qwen 3.8-Max ran 33 iterative cycles over a month of automated runs, achieving an Artificial Analysis score improvement from 40 to 45

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. A separate chip-design experiment involving more than 10,000 EDA tool calls over 60-plus hours demonstrated a 42% area reduction without performance loss

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Source: TechRadar

Source: TechRadar

Alibaba Cloud Targets 20GW of Datacenters by 2032

Alibaba Cloud aims to expand data center capacity past 20GW by 2032, a sixfold increase from its current approximately 4GW footprint

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. Citigroup estimates this capacity could generate more than $160 billion in external revenue for Alibaba Cloud

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. For context, commercial real estate firm Cushman and Wakefield reports 37.7GW of datacenters currently under construction in the United States alone

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. SpaceX had roughly 1.4GW of AI computing capacity mid-year with plans to exceed 10GW in 2027

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. Eddie Wu acknowledged that global shortages across the AI infrastructure supply chain are limiting how quickly Alibaba can scale its compute infrastructure

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. Alibaba Cloud plans to bring AI supernodes online at commercial scale this quarter, though Wu did not specify construction locations

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. Nomura expects future buildouts to blend owned, leased, and third-party-financed sites

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. Alibaba has committed more than $53 billion over three years to its AI expansion and raised approximately $10.2 billion in a follow-on share sale in August

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Source: Tom's Hardware

Source: Tom's Hardware

U.S. Export Controls Drive China's Self-Sufficiency Push

U.S. export controls keep Nvidia GPUs, particularly advanced Hopper products, largely out of China, forcing domestic companies toward self-sufficiency in AI hardware

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. Nvidia's latest 10-Q filing shows shipments of datacenter Hopper products to China were under 1% of its $89 billion in datacenter revenue for the quarter ending July 26

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. The same controls largely block Chinese firms from using TSMC for advanced chip manufacturing

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. Neil Shah, vice president at Counterpoint Research, told the Associated Press that using extra computing power to compensate for chip limitations helps China maintain strength locally

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. However, Counterpoint's Parv Sharma noted that narrowing the gap also depends on China's ability to advance its own foundries, not just chip design

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. Huawei unveiled competing chip technology at its Connect conference last week, having previously shelved its global Ascend rollout due to high domestic demand

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. The announcements came one day before Chinese President Xi Jinping's summit with President Donald Trump in Washington, where AI remains a top agenda item

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. Alibaba's Hong Kong-listed shares rose 5.1% on Tuesday following the Apsara Conference announcements

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