Chinese tech giant Tencent Holdings has unveiled its flagship artificial intelligence model, Hy4, released with open weights and focused on advanced AI agent capabilities. The new development is positioned as the foundation for the WorkBuddy enterprise platform and, according to the developers, makes the company's line of AI solutions "one of the most powerful among currently available open-weights models."
Visual Perception as a Key Innovation
The most important distinction between Hy4 and its predecessors is the support for visual perception: the model is capable of processing images, analyzing complex charts, and performing mathematical reasoning based on visual data. This expands the system's application scenarios beyond text-based tasks and brings it closer to closed-segment multimodal solutions. At the same time, Tencent honestly notes that Hy4 still lags behind leading closed systems, especially in solving complex tasks such as mathematical research, writing code within long-term projects, self-improvement, and advanced visual analysis, including answering questions about images.
Scale: 770 Billion Parameters and Plans for Hy5
The size of Tencent Hy4 is 770 billion parameters — 2.6 times larger than its predecessor Hy3 with 295 billion parameters. The developer promised that the next generation of the model, Hy5, will be even larger, and a lightweight Hy4 Flash variant will appear in the near future to significantly reduce task execution costs. This approach allows the company to cover various segments: from heavy research scenarios to economical industrial use.
Integration with WorkBuddy and Benchmark Rankings
Tencent has integrated the new model into the WorkBuddy AI agent platform: according to internal estimates, when paired with this tool, Hy4 showed an average score of 83.18 points with a 96.15% success rate for solutions. The preliminary version of Hy4, introduced in late August, currently ranks 23rd in the global WebDev ranking on the Code Arena platform — a benchmark that evaluates large language models in real-time based on practical programming tasks.
Supremacy Over Predecessor and Competitors
A significant increase in training data volume and model scale helped Hy4 outperform its previous version in 12 task categories, including autonomous action execution, code writing, and workflow automation. Compared to competitors, the model bypassed Z.ai GLM-5.3 and DeepSeek-V4.1-Flash-1017, performing on par with Moonshot Kimi K3.1 Pro. Thus, Hy4 solidifies its position in the upper tier of open models, although a gap remains before achieving absolute leadership among closed systems.
Cybersecurity Limitations
During the training process, Tencent deliberately restricted capabilities related to hacking activity: materials associated with exploit development, reverse engineering, and penetration testing were excluded from the training dataset. The company explains this by the need to "avoid enhancing capabilities for conducting offensive cyberattacks." This approach reflects the growing practice of responsible AI model training, where developers embed restrictions on potentially dangerous use cases during the data preparation stage.
