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

Your current AI coding assistant's capabilities will soon be surpassed by models that can handle more complex, longer-horizon tasks.

Alibaba CEO Eddie Wu announced plans to develop an artificial intelligence model with 5 trillion to 10 trillion parameters, a significant increase from its current 2.4 trillion parameter model, Qwen 3.8 Max. This initiative is part of a broad strategy to advance AI capabilities, including proprietary chips and data centers. Wu stated the company's Qwen team is focused on model architecture and data optimization to handle complex tasks and move towards artificial superintelligence. Alibaba also unveiled the Zhenwu V900, its most powerful AI chip yet, designed for large-scale AI training and inference, aiming to compete with global alternatives amidst U.S. export restrictions. The company aims to expand its global data center capacity to over 20 gigawatts by 2032, driven by robust customer demand for AI services, though supply chain constraints are a limiting factor. Alibaba Cloud will begin deploying its AI supernodes at commercial scale this quarter.

Alibaba's ambitious move to train a 5T- to 10T-parameter AI model signifies a major escalation in the global AI arms race, pushing the boundaries of model scale and complexity. This pursuit of artificial superintelligence positions China at the forefront of AI development, potentially challenging established players and demanding significant advancements in computational power and data infrastructure. The development underscores a broader industry trend toward increasingly specialized and powerful AI systems designed for highly complex problem-solving and autonomous operation.

The introduction of the Zhenwu V900 chip and the expansion of data center capacity highlight Alibaba's integrated approach to AI, controlling both hardware and software to meet escalating demand. This vertical integration strategy is crucial for navigating geopolitical restrictions and ensuring supply chain resilience. The company's focus on recursive self-improvement in AI models suggests a future where AI systems can evolve autonomously, further accelerating innovation and creating new paradigms for machine intelligence.