After the open source release of DeepSeek R1 attracted global attention, major technology companies have accelerated the launch of in-depth thinking models and planned to be open source. This trend marks a new stage of development in the field of artificial intelligence, with major companies competing to demonstrate their technological strength.
Alibaba Tongyi team recently launched a new in-depth thinking model QwQ-Max-Preview. This model not only has powerful reasoning capabilities, but also supports networked search functions. At present, this model has been launched on Tongyi Qianwen's new official website, and is planned to open source in the near future to provide convenience for more developers and users.
QwQ-Max-Preview is an inference model built on Qwen2.5-Max. Qwen2.5-Max is an important super-large-scale MoE model of Alibaba. After more than 20 trillion tokens of pre-trained data, it performed excellently in multiple benchmark tests, and even surpassed leading AI models such as DeepSeek V3 and GPT-4o, laying a solid foundation for QwQ-Max-Preview.
At present, the model is still in the preview stage. Alibaba Qwen team said it will continue to optimize it and plans to release the QwQ-Max official version in the future. At the same time, the team will also launch applications on Android and iOS, and will open the weights of QwQ-Max and Qwen2.5-Max based on the open source software license Apache 2.0. In addition, the team plans to release smaller models such as QwQ-32B for deployment on local devices.
The two core functions of QwQ-Max-Preview are in-depth thinking and network search. In terms of deep thinking, this model can conduct in-depth analysis of complex problems and provide detailed solutions. The network search function enables the model to break through the limitations of its own knowledge, obtain Internet information in real time, and assist in the reasoning process.
QwQ-Max-Preview demonstrates its powerful capabilities in multiple fields. In terms of mathematical understanding, it can deal with various problems from basic operations to complex mathematical competition questions, providing detailed problem-solving ideas and accurate answers. In terms of programming, whether it is simple scripts or complex application development, the model can handle it freely, outputting detailed code and attaching functional descriptions. In terms of logical reasoning, it can rigorously analyze problems and even propose multiple possibilities from the perspective of realistic logic to make the problems more perfect. In addition, the network search function enables the model to quickly query Internet information and reason based on real-time information to provide comprehensive answers.
QwQ-Max-Preview has a wide range of applicable scenarios. In educational learning scenarios, students can obtain detailed problem-solving ideas through this model to assist in learning subjects such as mathematics and programming. In creative work scenarios, writers and designers can use their network search capabilities to get inspiration and enrich their creative content. In game development scenarios, developers can use the capabilities of the model to design new gameplay and generate relevant code. In daily life, users can solve various problems through models, such as planning a trip or repairing home appliances. In industry research scenarios, researchers and analysts can use models to integrate industry dynamics and cutting-edge technologies to assist in writing research reports.
Using QwQ-Max-Preview is very simple. Users can access the Qianwen Chat Platform by visiting chat.qwen.ai, and enable in-depth thinking and network search functions. After entering the question, the model will think and reason and give detailed answers. If you are not satisfied with the results, the user can further refine the questions and ask questions again.
The QwQ-Max-Preview deep thinking model launched by Alibaba has opened a new door to AI experience for users with its outstanding capabilities in mathematics, programming, reasoning, and unique networked search and multimodal layout. Although it is currently in the preview stage and there may be some minor flaws in actual use, with the release of subsequent official versions and continuous optimization, I believe it will play a greater value in many fields such as education, creativity, and development.
Welcome to share your experience and suggestions in the comment section to witness the continuous growth and improvement of this model. We also look forward to Alibaba's continuous innovation in the field of AI to bring us more surprises and breakthroughs.