A major leap in open-source AI has arrived — Alibaba’s Tongyi Lab has unveiled Tongyi DeepResearch, a 30.5-billion-parameter agentic large language model that’s already outperforming Claude 4 Sonnet and other major contenders on key reasoning and search benchmarks.
What makes DeepResearch stand out
Unlike conventional LLMs, Tongyi DeepResearch is engineered for long-horizon, deep information-seeking tasks, allowing it to autonomously search, synthesize, and reason across vast datasets. Remarkably, it activates only 3.3 billion parameters per token, achieving exceptional efficiency without sacrificing capability.
The model demonstrates state-of-the-art performance on a range of agentic benchmarks — including Humanity’s Last Exam, BrowserComp, BrowserComp-ZH, WebWalkerQA, xbench-DeepSearch, FRAMES, and SimpleQA. In nearly all categories, Tongyi DeepResearch leads or matches top proprietary systems, confirming its robustness for complex, multi-step reasoning tasks.
100 % open-source and community-driven
True to its mission of open innovation, Alibaba has released Tongyi DeepResearch fully open-source, with model weights available on Hugging Face and ModelScope, and implementation code on GitHub, where it quickly became the #1 Trending Repository of the Day. The project builds on Alibaba’s earlier WebAgent framework, expanding its capabilities for autonomous browsing, fact retrieval, and contextual reasoning.
Why it matters
The arrival of DeepResearch signals a new phase for agentic AI — one where open-source models rival or surpass closed systems in research-grade reasoning. Its modular activation strategy also hints at a more sustainable path for large-scale deployment, balancing performance with compute efficiency.
As open-source ecosystems like Tongyi DeepResearch, Qwen3, and Mistral-Mixtral continue to evolve, developers gain unprecedented access to models capable of performing deep reasoning without enterprise-level compute budgets.
Explore the model:
🔗 GitHub Repository
🔗 Hugging Face Model Card
🔗 ModelScope Page
🔗 Alibaba Tech Blog
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