Tencent's Hy3 vs GLM-5.2 at half the size: wins except in code

The explosion of open-weight language models has transformed the landscape of enterprise artificial intelligence, but for a long time, licensing restrictions held back their adoption. The recent release of Hy3 by Tencent, under the permissive Apache 2.0 license, marks a before and after. This 295 billion parameter model in a Mixture-of-Experts architecture, with only 21 billion active per inference, directly competes with giants like GLM-5.2, which is twice its size. The big surprise is that Hy3 matches or surpasses its rival in search tasks, tool orchestration, and agents, although it gives ground in code generation. For companies evaluating deploying artificial intelligence in production, the key is not just in the benchmarks: Tencent has prioritized reliability metrics, reducing hallucinations from 12.5% to 5.4% and common sense errors by half. This makes Hy3 an ideal candidate for applications where precision is critical, such as customer service systems or automation of complex processes. Additionally, its memory footprint in FP8 is less than 300 GB, allowing it to run on affordable hardware, such as the H20 designed to comply with export restrictions, facilitating its deployment in cloud environments with AWS or Azure. At Q2BSTUDIO, we understand that each organization needs a unique AI strategy. That is why we offer artificial intelligence services for businesses that range from selecting the most suitable model to integrating it into real workflows. Our team helps design AI agents that interact with power bi tools and other data sources, always with a focus on cybersecurity and scalability. We also develop custom applications and custom software that incorporate these models, whether in AWS and Azure cloud services or on-premise infrastructure. Artificial intelligence ceases to be an experiment when it aligns with business objectives, and at Q2BSTUDIO we turn that promise into tangible results.