Recently, Tencent officially released the latest version of the Hunyuan big model series - Hunyuan-T1. This model is based on the Hunyuan medium-scale base. After large-scale post-training, it significantly improves its reasoning ability, especially in deep thinking and complex problem solving. Since the launch of Hunyuan T1-Preview in February this year, users have experienced a faster and deeper thinking process, and the launch of this official version marks a further upgrade of this series of products.
The research and development team of Hunyuan-T1 adopted the latest TurboS dock, an industry-leading ultra-large-scale Hybrid-Transformer-Mamba MoE model. TurboS shows unique advantages when dealing with long text inference, effectively solving the problems of context loss and long-distance information dependence. In addition, the Mamba architecture has also been specially optimized to significantly reduce the consumption of computing resources while maintaining information capture capabilities. According to official data, under the same deployment conditions, the decoding speed of Hunyuan-T1 is twice as fast.
In the post-training stage, the team invested 96.7% of computing power for reinforcement learning training, focusing on improving reasoning capabilities and optimizing alignment of human preferences. The team collected a large number of world science problems, covering fields such as mathematics, logical reasoning, science and code, to ensure that the model shows outstanding performance in various reasoning tasks. The course learning method is adopted in training to gradually increase the difficulty of data, so that the model can better cope with complex inference tasks.
Experience entrance: https://llm.hunyuan.tencent.com/?ref=producthunt#/chat/hy-t1