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Qwen Team Shaken: Key Researchers Resign Amidst Alibaba Reorganization

Qwen Alibaba AI Models Open Weight Models Large Language Models China Generative AI
March 04, 2026
Source: Simon Willison
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Shifting Sands
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Real Impact 7/10

Article Summary

Simon Willison reports on a concerning development in the open-weight AI model space. Alibaba’s Qwen team is experiencing a wave of resignations, triggered by a recent reorganization within the company. Lead developer Lin Junyang, instrumental in releasing Qwen’s open-weight models, stepped down, followed by several other core members responsible for key aspects of the Qwen models (e.g., code development, post-training research, and smaller model iterations). The catalyst appears to be a new researcher from Google’s Gemini team taking the lead, though specifics are still unfolding. Alibaba’s CEO was present at an ‘emergency All Hands’ meeting, indicating the company recognizes the gravity of the situation. This turmoil comes at a crucial time, as the Qwen 3.5 models—particularly the 27B and 35B iterations—are considered exceptionally good, especially considering their relative size. The team's ability to produce high-quality results from smaller models is a significant strength, and the departures threaten to derail that progress. The situation highlights the fragility of innovative AI projects within large, shifting corporate landscapes.

Key Points

  • Lead researcher Lin Junyang resigned, triggering a cascade of departures from the Qwen team.
  • The resignation wave appears linked to a new Google Gemini researcher taking the lead on Qwen.
  • Alibaba’s CEO attended an emergency meeting to address the situation, highlighting its significance.

Why It Matters

This news is more than just a personnel shuffle; it directly impacts the trajectory of a promising open-weight AI model family. Qwen’s success has been built on a focused effort to produce high-quality models across a range of sizes, particularly the 27B and 35B iterations, which have demonstrated notable performance despite their relatively small footprint. The loss of these key researchers, combined with the shift in leadership, introduces considerable uncertainty regarding the future development and maintenance of the Qwen models. For professionals in AI research and development, this situation serves as a cautionary tale about the risks involved in relying on a single team within a large organization. It also underscores the importance of robust intellectual property rights and organizational structures to protect innovative projects.

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