Tencent's new ultra-large model 'Hunyuan-T1', powered by its Mamba framework, marks another significant entry in the rapidly evolving AI landscape. This model demonstrates considerable performance, underscoring the importance of reinforcement learning in optimizing AI systems. However, some skepticism exists about the reliability of performance metrics, especially concerns around Goodhart's law, which posits that performance indicators might not accurately reflect genuine improvement. Additionally, the naming conventions of such models can cause confusion, highlighting cultural nuances in branding. As more Chinese products enter the global market, names and their meanings become pivotal in user recognition. Comments also stress the need for higher quality in communications and documentation related to AI models, provoking discussions about whether language discrepancies stem from model-generated content or human error. These observations collectively highlight the challenges and expectations from newly released AI technologies, especially in terms of transparency and communication.