Tencent 发布 Hy4，强大的前沿 LLM引入视觉理解和计算机使用
Tencent Holdings Ltd. 今天的推出 Hy4，是一种新的大型语言模型，新增计算机首次能够使用，使用先进的视觉理解，推理和工具调用来提供长视距代理性能。
公司称的模型标志着比其Hy4预览(Hy4 Preview)的性能有了显著的飞跃，它于8月28日到达，重达7700亿参数，活性参数达490亿。 两者都提供了100万个令牌上下文窗口，将其与来自欧洲和中国开发商的当前开放权重前沿模型，包括Mistral AI SAS，北京Moonshot技术有限公司和Z.AI有限公司的相同范围。
称公司大幅度扩大了培训前和培训后两个阶段的规模，在随后的教学中报告预览版的收益、长文理解、代理长视距任务和深入研究。 Tencent还查明了前一版本 " 思考 " 过程中的过度推理和过度核查。
新的模式主要侧重于工作场所协作的现实世界生产力、人类经验和专业工作。 称公司优化了长文本学习能力，以理解复杂的信息，包括网络开发，文档汇总，视觉创作任务，文档展示等等。
该公司补充说，它还加强了前端和游戏开发能力，包括复杂业务逻辑、国家管理和管弦乐在内的高度复杂任务。 一些模型在生产状态，优雅和美丽的用户界面上挣扎，这些界面是可视化的，同时也是功能完备的。
专业游戏开发者，行业工程师和业余风情编码师将AI模型作为其作品的一部分并不罕见。 然而，最近一阵喷泉开始有编码器开始复制，反向工程师和克隆老旧和半最新电子游戏。 这导致Anthropic PBC阻止Claude Code及其基础Opus 5.5模型协助完成这些任务。
称公司与Unreal Engine,Unity,Godot等主要引擎深度融合，使其具备支持复杂游戏逻辑和多人执行的能力。 与预览相比，Tencent 称 Hy4在GameDev板凳上改进了19.1%，在GameLogic 基准测试上则改进了9.8%，尽管实际基准数仍然是内部的，而不是发布。
为了推进科学推理，Tencent推进了下一阶段的递归自我提升，以提高研发能力。 该模型使用Hyra 2.0拉带，一个自主的AI研究agent系统，优化了较小的模型共享同一架构的培训前基础设施。
目前，该模型可在Tencent Cloud TokenHub、WorkBuddy、CodeBuddy、Yuanbao、WeCom的AI助理、Ima等网站上找到。 也可以通过OpenRouter,Hermes和OpenCode等第三方来源访问。 该公司补充说，尽管它比Hy4预览有显著的改进，但它保持了较低的成本，将相同的定价维持在每百万美元输入令牌约90美元，每百万产出令牌约270美元，每百万缓存输入令牌约0.45美元。
该模型的Flash版本预定很快发布，以提高用户的成本效率。 该公司还打算在未来几天内发布模型权重和系统卡片，作为其负责任的开源 AI开发承诺的一部分。
图片：Tencent
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Tencent releases Hy4, powerful frontier LLM introducing visual understanding and computer use
Tencent Holdings Ltd. today introduced Hy4, a new large language model that adds computer-use capabilities for the first time, using advanced visual understanding, reasoning and tool-calling to deliver long-horizon agentic performance.
The company said the model marks a significant leap in performance over its Hy4 Preview, which arrived August 28, weighing in at 770 billion parameters with 49 billion active parameters. Both provide a 1 million token context window, putting it in the same range as current open-weights frontier models from European and Chinese developers, including Mistral AI SAS, Beijing Moonshot Technology Co. Ltd. and Z.AI Co. Ltd.
The company said it substantially scaled both pre-training and post-training, reporting gains over the preview version in instruction following, long-context understanding, agentic long-horizon tasks, and deep research. Tencent also identified excessive reasoning and over-verification during the previous version’s “thinking” processes.
The new model focuses heavily on real-world productivity for workplace collaboration, human experience and professional work. The company said it optimized long-context learning capabilities to understand complex information, including web development, document summarization, visual creative tasks, document presentation, and more.
The company added that it also enhanced its capability for front-end and game development, high-complexity tasks that include intricate business logic, state management, and orchestration. Some models struggle with producing stateful, elegant and beautiful user interfaces that are visually polished and also fully functional.
It is not uncommon for professional game developers, industry engineers and amateur vibe coders to use AI models as part of their work. However, a recent spate has had coders begin to reproduce, reverse engineer and clone older and semi-recent video games. This caused Anthropic PBC to block Claude Code and its underlying Opus 5.5 model from assisting in these tasks.
The company said it integrated deeply with major engines such as Unreal Engine, Unity, and Godot, giving it the capability to support complex game logic and multiplayer implementations. Compared to the preview, Tencent said Hy4 improved by 19.1 percent in the GameDev bench and 9.8 percent in GameLogic benchmarks, although the actual baseline numbers remain internal and weren’t released.
To advance scientific reasoning, Tencent advanced the next stage of Recursive Self-Improvement to enhance research and development capabilities. Using the Hyra 2.0 harness, an autonomous AI research agent system, the model optimized the pre-training infrastructure for smaller models sharing the same architecture.
The model is currently available on Tencent Cloud TokenHub, WorkBuddy, CodeBuddy, Yuanbao, WeCom’s AI Assistant, Ima and more. It can also be accessed via third-party sources such as OpenRouter, Hermes and OpenCode. The company added that, despite its significant enhancements over Hy4 Preview, it kept costs low, maintaining the same pricing at around $0.90 per million input tokens, $2.70 per million output tokens, and $0.045 per million cached input tokens.
The Flash version of the model is scheduled for release soon to deliver greater cost efficiency for users. The company also said it intends to release the model weights and system cards in the coming days as part of its commitment to responsible open-source AI development.
Image: Tencent
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