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Home » Alibaba releases open-source AI agent to rival OpenAI’s flagship Deep Research
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Alibaba releases open-source AI agent to rival OpenAI’s flagship Deep Research

adminBy adminSeptember 18, 2025No Comments2 Mins Read
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Alibaba Group Holding has unveiled a “leading open-source deep research” artificial intelligence agent that it says matches the performance of OpenAI’s flagship Deep Research tool, while being more efficient.
The agent has been integrated into Alibaba’s maps app, Amap, and its AI-powered legal research tool, Tongyi FaRui, according to a blog post on Tuesday by Alibaba’s AI search development team, Tongyi Lab. Alibaba owns the South China Morning Post.

Users of Amap can leverage the deep research agent’s web retrieval capabilities to plan multi-day trips. Meanwhile, Tongyi FaRui has been updated with the agent’s research functions, enhancing its ability to retrieve case law with verified citations, according to Alibaba.

The agent is the latest addition to Alibaba’s rapidly expanding AI initiatives. In the past two weeks alone, the company has launched its first trillion-parameter base model, Qwen-3-Max-Preview, along with Qwen3-Next-80B-A3B – a smaller yet more powerful model, according to benchmarking firm Artificial Analysis.

Deep research agents are AI tools designed to perform complex web retrieval tasks that require multiple steps. The first such agent, OpenAI’s Deep Research, was launched and integrated into ChatGPT in February. Other major US tech companies, including Google DeepMind, have also introduced similar tools.

OpenAI CEO Sam Altman attends a UK state banquet at Windsor Castle on Wednesday. The company released the world’s first deep research agent in February. Photo: Reuters
OpenAI CEO Sam Altman attends a UK state banquet at Windsor Castle on Wednesday. The company released the world’s first deep research agent in February. Photo: Reuters

Alibaba said its deep research agent showed “incredible efficiency” compared with US proprietary tools, as it had only 30 billion parameters – significantly fewer than the estimated parameter counts of the models driving US deep research agents.



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