Tencent Upgrades Self-Developed Foundation Model Tencent Hunyuan and Deploys it to Internal Products


Tencent Hunyuan releases the ultra-small model HY-1.8B-2Bit, which reduces the equivalent parameter count to 0.3B through an industrial-level 2Bit quantization scheme, with memory usage of approximately 600MB and a size smaller than some mobile applications. This technological breakthrough solves the problem of significant precision loss in low-bit quantization, providing a new approach for efficient deployment of large models on consumer-grade hardware.
AI expert Peng Tianyu joins Tencent Hunyuan as Chief Research Scientist and Head of Multi-modal Reinforcement Learning Technology, responsible for building top-tier teams to tackle cutting-edge challenges in multi-modal generation and understanding. Peng Tianyu is a direct Ph.D. student from the Department of Computer Science at Tsinghua University, mentored by Professor Zhu Jun, with a strong academic background.
The Tencent Hunyuan team has open-sourced the Hunyuan Image 3.0 image-to-image model, which has 80 billion parameters and uses a mixture-of-experts architecture, ranking seventh in global image editing rankings. Its core breakthrough lies in the multimodal architecture of "thinking first, then editing," making it currently the strongest open-source image-to-image model in the world.
Tencent Hunyuan open-source translation model version 1.5 introduces 1.8B and 7B models, focusing on efficiency and high-quality translation with optimized cloud-device synergy. The 1.8B model is designed for mobile devices, requiring only 1GB memory for offline operation, enabling on-device deployment and excellent performance.....
Recently, the Tencent Hunyuan team released their latest research findings on their official WeChat account —— SRPO (Semantic Relative Preference Optimization), aimed at improving the realism of AI-generated images, especially addressing the 'oily' issue in the skin texture of the open-source text-to-image model Flux. This innovative technology is expected to bring about revolutionary changes in the image generation field. In today's era where digital art is becoming increasingly popular, the quality of AI-generated images has become particularly important. The Flux model, as a popular foundation model in the open-source text-to-image community, is often criticized for its