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信创模盒+摩尔线程|完成逾百个模型适配 量化模型优势显著
智通财经网· 2025-11-25 07:05
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 ...
完成逾百个模型适配 量化模型优势显著
Zhi Tong Cai Jing· 2025-11-25 07:04
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]