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Alibaba unveils next-gen chip for agentic AI: company

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By Reuters | Updated: March 24, 2026

BEIJING, March 24 (Reuters) – Alibaba (9988.HK) on Tuesday revealed its next-generation XuanTie C950 5-nanometer processor at an internal conference, the company said ​in a blog post, as the Chinese tech giant gears up ‌for the shift towards agentic AI.

The 3.2 GHz server chip, built using open-source RISC-V chip architecture, was billed as “the highest performing RISC-V CPU in the world” ​at a conference hosted by DAMO Academy, Alibaba’s research arm, ​according to Chinese media reports.

The chip performs more than three ⁠times faster than its predecessor, the XuanTie C920, the reports said.

The ​company did not reveal which fab manufactured the chip.

“RISC-V’s open-standard nature allows ​chip designers to customize instruction sets and accelerate specific AI workloads with no or low licensing fees. This is particularly important for the development of AI ​agents,” the blog post said.

Alibaba is accelerating in-house chip development through ​its T-Head semiconductor arm, primarily focusing on the Zhenwu 810E chip series for AI ‌training ⁠and inference, while the XuanTie series is focused on high-performance cloud systems and agentic AI.

The move comes after Alibaba last week launched Wukong, its enterprise platform optimised for AI agent workflows, as companies and institutions ​throughout China adopt OpenClaw.

Its ​international equivalent, Accio ⁠Work, was launched on Monday. The agentic AI platform says it can autonomously run complex business operations ​for small and medium-sized enterprises.

The firm reorganised some of ​its AI-focused ⁠teams under the newly created Alibaba Token Hub earlier this month, which focuses on building AI work platforms for enterprises.

The business strategy shift ⁠comes as ​Alibaba finds new ways to ensure ​profitability as Chinese AI models’ token prices have dropped dramatically amid fierce domestic competition.

Reporting by ​Laurie Chen and Che Pan; Editing by Kevin Buckland and Thomas Derpinghaus

© Thomson Reuters 2026