Tencent Hunyuan Hy4 Official Version Released, Introducing Vision and Computer Operation Capabilities for the First Time
Tencent Hunyuan has released the official version of the Hy4 large language model. Compared with Hy4 preview, it significantly expands the scale of pre-training and post-training, introduces vision capabilities for the first time, and supports computer operation, enabling it to complete tasks by combining command-line and graphical interfaces. Hy4 is now available on Tencent Cloud and OpenRouter, and can be experienced in products such as CodeBuddy / WorkBuddy, Yuanbao, and ima, while maintaining the same API pricing as the preview. The official team plans to open-source the model weights and release a model system card in the near future, while also stating that Hy4 still has a considerable gap compared with top closed-source models on highly difficult test sets such as frontier mathematics, long-horizon development, and visual question answering.
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The original text explains the capability expansion of Hy4 relative to the preview, its launch channels, and open-source plans, from which the gap between open-source models and closed-source frontier models can be judged.
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Tencent Hunyuan Hy4 Official Version Released, Claimed to Be the First to Rank Among the Strongest Open-Source Models, Born for Real Productivity
2026-11-04 12:59 IT Home - Qingyuan
Thanks to IT Home users Zhixia, Domado, McWings, xxy171070, Alita's Fanboy, Chigua Qunzhong_, Yae Miko, and Weiyang for the tip-offs!
IT Home, November 4 news: Tencent Hunyuan today (the 4th) released the official version of its latest-generation large language model, Hy4. According to the official announcement, with the model's capabilities once again comprehensively upgraded, Hy is for the first time ranked among the strongest open-source models. Hy4 will soon open-source its model weights, publish a model system card, and actively advance more responsible open-sourcing, with a focus on risks such as cyber and biosecurity.
Compared with Hy4 preview, Hy4 has significantly expanded the scale of pre-training and post-training, introduced visual capabilities for the first time, and greatly improved comprehensive capabilities including instruction following, long-document understanding, long-horizon tasks, and deep research.
Hy4 introduces visual capabilities for the first time, enabling fine-grained image processing, complex chart analysis, and mathematical visual reasoning by combining perception, reasoning, and tool calling. Hy4 also supports computer operation for the first time, allowing flexible combined use of the command line and graphical interface. Tencent also conducted specialized training for professional software such as Blender and CAD and for cross-application long-horizon tasks, continuously optimizing the planning and execution of professional tasks.
According to the introduction, the model can be used in scenarios such as visual and computer tasks, front-end and game development, finance and office scenarios, scientific research and model R&D, and long-term personal assistants, being born for real productivity.
As IT Home previously reported, on August 28, Tencent released Hy4 preview, with 770 B total parameters, 49 B activated parameters, and a context length of 1M.
Officials stated at the time that Hy4 preview had significantly expanded in model size, context length, and data scale, and that the joint progress of pre-training and post-training brought another huge improvement in intelligence level.
Currently, Hy4 is available on Tencent Cloud and OpenRouter, and can be experienced on products such as CodeBuddy / WorkBuddy, Yuanbao, and ima. While its performance significantly exceeds that of Hy4 preview, it maintains the same API price.
Officials plan to open-source the model weights and have partnered with the vLLM/SGLang community and Inferact Inc. to provide open-source ecosystem support. A model system card is also planned for release at that time, including details such as more comprehensive safety evaluations.
Although Hy4 is already one of the strongest open-source models currently available, there is still a considerable gap between it and top closed-source models, especially on high-difficulty test sets in areas such as frontier mathematics, long-horizon development, model iteration, and visual question answering that are built internally. Tencent Hunyuan stated that it will continue to steadily expand the scale of pre-training and post-training and strive to narrow the gap with top closed-source models.
Hy4 flash is also planned for release in the near future, which will significantly improve the model's cost-effectiveness and inference speed, and enable more frequent collaborative iteration with products to continuously improve practicality.