Core Insights - The launch of "ModelHub XC" by Paradigm Intelligence has achieved over 1,000 model adaptations within two months, four months ahead of schedule, marking significant progress in the domestic AI ecosystem [1][11] - The platform supports a diverse range of models, including general large language models, specialized vertical models, and cutting-edge innovative models, providing a solid foundation for the coordinated development of domestic AI software and hardware [1][12] Development Timeline - **Launch Date**: The platform was officially launched on September 22, 2025, addressing the compatibility issues between deployed models and underlying chip architectures, which has been a barrier to the large-scale implementation of AI [2][12] - **Vertical Model Adaptation**: On October 17, 2025, the platform completed the adaptation and deep optimization of the wind tunnel calculation model on the domestic chip Xiwang S2, achieving commercial-grade performance [4] - **Frontier Model Adaptation**: On November 1, 2025, the innovative model DeepSeek-OCR was successfully adapted for testing on various domestic computing cards, showcasing significant technical innovation [6] - **Agent Model Deployment**: On November 17, 2025, the efficient agent model MiniMax-M2 was adapted for deployment on the Ascend 910B4 chip, demonstrating global leadership in model capabilities [7] - **Batch Adaptation Achievement**: On November 25, 2025, the platform achieved large-scale adaptation of 108 models on the Moer Thread chip, highlighting its strong ecological expansion capabilities [9] Platform Capabilities - The platform is driven by the EngineX engine, enabling "plug-and-play" deployment of models on domestic chips, significantly shortening deployment cycles and resolving compatibility issues [12] - The model ecosystem is rich and diverse, covering a wide range of models and supporting major domestic computing platforms [12] - The platform offers professional services for model adaptation, backed by a team of hundreds of engineers to ensure successful adaptation and stable operation in domestic environments [12] Future Outlook - The platform aims to accelerate towards a "ten thousand model" ecosystem within a year, continuing to expand model scale and chip support [14] - The company plans to maintain a rapid update pace to build a more complete and efficient domestic AI infrastructure [14]