智通财经APP获悉，范式智能近日宣布，「信创模盒」ModelHub XC已完成108个主流AI模型在摩尔线程GPU上的适配认证，涵盖文本生成、视觉理解、多 模态问答等多种任务类型，预计未来半年内将扩展至千量级，为国产算力生态注入持续动能。 值得一提的是，在本次批量适配过程中，作为年内登陆科创板的国产GPU企业，摩尔线程的硬件在量化模型方面展现出显著优势。其GPU凭借对低精度数据 类型的硬件级支持、优化的指令集与缓存机制，有效降低了模型显存占用并提升推理速度，使量化模型在实际部署中兼具效率与能效。通过精细化校准与优 化，适配模型在性能提升的同时，也确保了推理精度满足商业落地要求。据报道，摩尔线程在11月24日正式启动科创板发行，发行价为114.28元/股，创下 2025年以来A股新股发行价新高。 在AI推理效率成为产业落地核心挑战的今天，如何实现模型在国产芯片上的高效、稳定运行，已成为推动算力生态走向成熟的关键。作为应对，范式智能 依托自研的EngineX引擎技术，重点突破模型在国产芯片上的兼容性与运行效率，显著降低开发者的部署门槛。 目前，「信创模盒」ModelHub XC已完成包括Mata、千问、Deeps ...

Core Insights - Paradigm Intelligence recently announced that its "ModelHub XC" has completed the adaptation certification of 108 mainstream AI models on Moore Threads GPUs, covering various task types such as text generation, visual understanding, and multimodal Q&A, with plans to expand to a thousand models in the next six months, injecting continuous momentum into the domestic computing power ecosystem [1][3] - Moore Threads, a domestic GPU company set to launch on the Sci-Tech Innovation Board, has demonstrated significant advantages in quantized models during this adaptation process, with its GPUs effectively reducing model memory usage and enhancing inference speed through hardware-level support for low-precision data types and optimized instruction sets [1] - The official launch of Moore Threads on the Sci-Tech Innovation Board is scheduled for November 24, with an issuance price of 114.28 yuan per share, marking a new high for A-share IPO prices since 2025 [1] - The efficient and stable operation of models on domestic chips is a key challenge for the industry, and Paradigm Intelligence is addressing this by leveraging its self-developed EngineX engine technology to improve model compatibility and operational efficiency on domestic chips, significantly lowering deployment barriers for developers [1][5] Summary by Sections ModelHub XC Overview - ModelHub XC is an AI model and tool platform aimed at the domestic computing power ecosystem, providing a comprehensive solution that covers the entire process from model training and inference to deployment, while also serving community and service functions [5] EngineX Engine - The EngineX engine serves as the underlying support system for ModelHub XC, enabling "engine-driven, multi-model plug-and-play" capabilities, effectively addressing the bottlenecks in model compatibility and scale support on domestic chips [3][5]

Core Insights - Fourth Paradigm launched the "ModelHub XC" platform, addressing industry pain points by breaking down barriers between clients, computing power, and developers [1] - The "ModelHub XC" features an AI engine system called EngineX, which adapts various models to domestic computing power, reducing time and repetitive labor [1] - The platform currently supports over 100 certified models and aims for rapid updates in the number of adapted models [1] Group 1 - The "ModelHub XC" provides a wide variety of downloadable models, with a focus on adapting to domestic computing power [1] - The platform has already adapted to several mainstream domestic computing powers, including Huawei Ascend, Cambricon, and others, with plans to cover more in the future [1] - Fourth Paradigm offers value-added services for model adaptation, ensuring that users can have models adjusted to fit specific domestic computing power needs [1]

Core Insights - Fourth Paradigm launched the "ModelHub XC" platform, along with a community and value-added services for model adaptation, aiming to address compatibility issues between domestic AI models and chips [1] - The introduction of EngineX, an AI engine system specifically designed for domestic computing power, facilitates batch model support and reduces deployment time, promoting a "plug-and-play" model approach [1] - Fourth Paradigm's value-added services, supported by hundreds of engineers, ensure model adaptation to specified domestic computing power, with over a hundred certified models currently and a target of reaching hundreds of thousands within a year [1] Industry Context - Compatibility issues between models and chips in the domestic computing ecosystem often lead to prolonged deployment cycles and increased redundancy in work [1] - The launch of "ModelHub XC" aims to bridge the gap between computing power and models, potentially providing critical support for the large-scale implementation of AI in the industry [1]

Core Viewpoint - The emergence of compatibility issues between deployed AI models and chip architectures is becoming a hidden ceiling that restricts the practical application of AI, which Fourth Paradigm aims to address with its new solutions [1][7]. Group 1: Product Launch - Fourth Paradigm officially launched the "ModelHub XC" platform, the "Xinchang Community," and the "Xinchang Model Adaptation Value-Added Service" to tackle industry pain points and bridge gaps between customers, computing power, and developers [3]. - The "ModelHub XC" features an innovative AI engine system, EngineX, specifically designed to adapt to domestic computing power, fundamentally addressing the long-standing compatibility and support issues of domestic AI models [7]. Group 2: Market Context - Many existing ModelHubs primarily optimize foreign models and software for their hardware (e.g., NVIDIA GPUs), leading to compatibility issues with domestic hardware (e.g., Cambricon), resulting in time-consuming and repetitive adaptation processes [8]. - The platform has already certified and adapted over a hundred models upon launch, with plans to increase this number to thousands within six months and to reach tens of thousands within a year [10]. Group 3: Services and Support - Fourth Paradigm introduced a value-added service for model adaptation, providing tailored adjustments for users unfamiliar with which models are compatible with domestic computing power, ensuring a "safety net" for model compatibility [12]. - The platform also offers clear labeling of compatible domestic chip brands for each model, simplifying the process for users to determine which chips to purchase based on the models they wish to download [10].