The video reviews Hy3, a new 295 billion parameter open-source AI model released by Tencent, the largest gaming and Chinese company. Positioned as a competitor to models like DeepSeek and Qwen, Hy3 boasts a liberal Apache 2 license allowing commercial use. Benchmark tests show Hy3 performing exceptionally well, surpassing DeepSeek V4 Pro in math and long-context reasoning tasks, and ranking highly on open-source leaderboards. The model supports various “thinking modes” that enhance its reasoning capabilities, with higher modes producing more detailed and extensive outputs.
The reviewer demonstrates Hy3’s capabilities through a series of practical tests, including coding, logic puzzles, and game development prompts. For example, the model successfully generates playable game prototypes like Flappy Bird and a basic Outrun-style racing game, with higher thinking modes significantly improving complexity and functionality. It also produces impressive 3D interactive web pages, such as a detailed Earth model with adjustable features, showcasing its ability to handle creative and technical tasks effectively.
Hy3’s text generation quality is highlighted through tasks like creating photo-realistic human face renders and complex HTML canvas animations. While the UI and visual polish of generated applications are basic, the underlying code is functional and free of runtime errors. The model respects prompt instructions well, especially regarding token limits and thinking modes, and can scale between local and cloud-based deployments depending on user hardware capabilities.
An interesting aspect covered is Hy3’s handling of images, despite being primarily a text inference model. It uses OCR and metadata classification to interpret images, enabling it to generate related content like animated 3D voxel versions of images based on classification tags. This workaround allows some level of image understanding and generation, although it does not directly process image pixels. This feature adds versatility to the model’s applications beyond pure text tasks.
Finally, the video explores Hy3’s performance on complex mathematical problems and reasoning puzzles, where it excels with thinking modes enabled, often outperforming other open-source models and approaching proprietary ones like Qwen 3.7. The model also demonstrates ethical reasoning by avoiding inappropriate suggestions in sensitive scenarios. The reviewer concludes that Hy3, with its strong benchmarks, open licensing, and scalable deployment options, could be a promising new open-source alternative to Qwen 3, especially for agentic and reasoning-heavy applications.
