Recently, Tencent released the official version of its Hunyuan large model series – Hunyuan-T1. This new model, built upon the Hunyuan medium-scale base, has undergone extensive post-training, significantly enhancing its reasoning capabilities, especially in deep thinking and complex problem-solving. Since the launch of the Hunyuan T1-Preview in February, users have experienced faster and more profound thought processes. The release of the official version marks a further upgrade of the product series.
The Hunyuan-T1 development team utilized the latest TurboS base, a leading ultra-large-scale Hybrid-Transformer-Mamba MoE model. TurboS demonstrates unique advantages in handling long-text reasoning, effectively addressing issues of context loss and long-distance information dependencies. Furthermore, the Mamba architecture has been specifically optimized to significantly reduce computational resource consumption while maintaining information capture capabilities. According to official data, under the same deployment conditions, Hunyuan-T1's decoding speed is twice as fast.
During the post-training phase, the team invested 96.7% of its computing power in reinforcement learning training, focusing on improving reasoning capabilities and aligning with human preferences. The team collected a large number of world-class science problems, covering mathematics, logical reasoning, science, and coding, ensuring the model's excellent performance in various reasoning tasks. A curriculum learning approach was adopted during training, gradually increasing data difficulty.
Experience it here: https://llm.hunyuan.tencent.com/?ref=producthunt#/chat/hy-t1
