Alibaba CEO Eddie Wu says the company plans to train a 5T- to 10T-parameter AI model, as it lays out a sweeping push across AI models, chips, and data centers
Alibaba Group (9988.HK) plans to train a new artificial intelligence model with 5 trillion to 10 trillion parameters …
Reuters
Context & Ripple Effects
Alibaba has moved Qwen from a broad open-source Qwen 2.5 release in 2024 to its first model above one trillion parameters in 2025, then to a 2.4-trillion-parameter Qwen3.8 Max preview in July 2026. The new target extends that scaling path rather than marking a standalone model launch.
The model plan is paired with Alibaba's earlier more-than-$53 billion AI-infrastructure commitment and T-Head’s successive training accelerators, including the Zhenwu M890. That combination makes compute supply and data-center buildout central to whether Qwen can be trained and deployed at the intended scale.
First-order effects
Alibaba commits Qwen to a 5T- to 10T-parameter training target, raising the compute, data-center, and accelerator capacity required for its next frontier-model cycle.
T-Head’s V900 becomes a strategic part of Alibaba’s AI stack alongside its models and data centers, rather than only a component offering.
Second-order effects
Alibaba’s data-center program must translate from a capital pledge into sustained capacity for training and inference if the larger Qwen target is to be met, increasing the operational importance of its chip roadmap.
The company’s model, chip, and infrastructure units face tighter coordination requirements: accelerator performance, cluster scaling, and model-training ambitions are no longer separable product tracks.
Third-order effects
If Alibaba can execute across all three layers, frontier AI competition shifts further from standalone model releases toward vertically integrated compute platforms controlled by a small number of capacity operators.
Ever-larger parameter targets make access to durable data-center and accelerator capacity a defining constraint on who can sustain frontier-model development.
The trend: Alibaba’s announcement is part of AI industrialization in which model ambitions, proprietary chips, and data-center capacity are being assembled into a single competitive system.
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@hsu_steve Impressive—only a year behind (at most) NVIDIA B200 widescale deployment. Not equivalent (quite) but in the ballpark—and much faster than I for one thought possible.
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