Introduction We present Tongyi DeepResearch , an agentic large language model featuring 30 billion total parameters, with only 3 billion activated per token. Developed by Tongyi Lab, the model is specifically designed for long horizon, deep information seeking tasks. Tongyi DeepResearch demonstrates state of the art performance across a range of agentic search benchmarks, including Humanity's Last Exam, BrowserComp, BrowserComp ZH, WebWalkerQA, GAIA, xbench DeepSearch and FRAMES. More details can be found in our 📰 Tech Blog. Key Features ⚙️ Fully automated synthetic data generation pipeline : We design a highly scalable data synthesis pipeline, which is fully automatic and empowers agentic pre training, supervised fine tuning, and reinforcement learning. 🔄 Large scale continual pre training on agentic data : Leveraging diverse, high quality agentic interaction data to extend model capabilities, maintain freshness, and strengthen reasoning performance. 🔁 End to end reinforcement learning : We employ a strictly on policy RL approach based on a customized Group Relative Policy Optimization framework, with token level policy gradients, leave one out advantage estimation, and selecti…
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