Core Insights - Baidu officially open-sourced the Wenxin large model 4.5 series on June 30, which includes 10 models with mixed expert (MoE) architecture and dense models, featuring 47 billion and 0.3 billion parameters respectively [1] - The open-sourced models are available for download and deployment on platforms like PaddlePaddle and HuggingFace, with API services accessible through Baidu's intelligent cloud [1] - The Wenxin model 4.5 series introduces an innovative multi-modal heterogeneous model structure, enhancing multi-modal understanding while maintaining or improving text task performance [1] Group 1 - The Wenxin model 4.5 series is fully open-sourced under the Apache 2.0 license, supporting academic research and industrial applications [1] - Baidu has achieved a "dual-layer open-source" strategy with both framework and model layers, establishing a significant AI full-stack technology advantage [2] - PaddlePaddle, as China's first self-developed and open-source industrial-grade deep learning platform, has been enhanced with the release of the Wenxin model development suite ERNIEKit and the efficient deployment suite FastDeploy [2] Group 2 - The open-sourced series is designed to lower the barriers for post-training and deployment, being widely compatible with various chips [1][2] - The advancements in the Wenxin model 4.5 series are attributed to key technologies such as multi-modal mixed expert model pre-training and efficient training inference frameworks [1]