推理性能实现跨越：摩尔线程联合硅基流动，在DeepSeek R1 671B全量模型上实现性能突破，MTT S5000单卡Prefill吞吐突破4000 tokens/s、Decode吞吐突破1000 tokens/s，树立国产推理性能标杆。 全新个人智算平台：正式发布搭载智能SoC芯片"长江"的AI算力本MTT AIBOOK，迷你型计算设备 MTT AICube。 （文章来源：21世纪经济报道） 12月20日，摩尔线程于北京举办首届MUSA开发者大会。会上，摩尔线程展示了其基于MUSA统一架构 为核心的全栈技术成果，并在现场展示落地成果。包括： "夸娥万卡"高效训练：发布夸娥万卡智算集群，展示了其支撑万亿参数模型训练的工程化能力与可靠 性，在多项关键精度指标上达到国际主流水平。 ...

据智通财经报道，摩尔线程成立于2020年，主要业务是全功能GPU的设计与研发。五年时间，其已构建 了从芯片、板卡到大规模集群及软件方案的全栈布局，业务场景全面覆盖"云边端"。此前，12月5日， 摩尔线程以114.28元发行上市，上市首日大涨425%。 【#摩尔线程AI电脑预售价9999元#，为AI算力笔记本MTTAIBOOK】 据红星资本局报道，摩尔线程创始人、董事长兼CEO张建中12月20日在摩尔线程首届MUSA开发者大会 上发布AI算力本MTTAIBOOK笔记本。目前该笔记本已在京东开放预售，32GB、1TB 版本预售价9999 元。 记者了解到，该笔记本搭载摩尔线程新发布的自主研发智能SoC 芯片"长江"，集成高性能全大核CPU， 以及摩尔线程全功能GPU，支持MUSA 统一架构，异构AI算力达50TOPS。该笔记本集开发、办公、娱 乐等于一体，支持Windows虚拟机、Linux、安卓容器以及所有的国产操作系统。 ...

Core Insights - The first MUSA Developer Conference showcased the launch of the new GPU architecture "Huagang" by Moore Threads, along with AI training and inference chip "Huashan" and high-performance graphics rendering chip "Lushan" [1][4][5][7] - Moore Threads introduced the "Kua'e" supercomputing cluster, featuring the self-developed "Yangtze" intelligent SoC chip, aimed at enhancing AI computing capabilities [1][9] Group 1: New GPU Architecture and Chips - The "Huagang" GPU architecture features a 50% increase in computing density and supports full precision end-to-end calculations from FP4 to FP64, with new asynchronous programming models and MTLink high-speed interconnect technology for scaling over 100,000 cards [4][14] - The "Huashan" chip focuses on AI training and inference, integrating new asynchronous programming and full precision tensor computing units, supporting large-scale intelligent computing clusters [5] - The "Lushan" chip specializes in high-performance graphics rendering, achieving a 64x increase in AI computing performance, 16x in geometric processing, and 50x in ray tracing performance, catering to AAA games and high-end graphics creation [7] Group 2: Collaborations and Ecosystem Development - Several companies listed on the Sci-Tech Innovation Board, including Dahong Technology and Zhongwang Software, are collaborating with Moore Threads to leverage its GPU for high-performance needs such as ultra-high-definition live streaming and offline video enhancement [3] - The MUSA software architecture has been upgraded to version 5.0, enhancing compatibility with programming languages like TileLang and Triton, and achieving over 98% efficiency in core computing libraries [12] Group 3: Industry Challenges and Future Directions - The need for a unified or highly compatible interface standard for domestic GPU chips is emphasized to avoid fragmentation and inefficiencies in the software ecosystem [13] - The transition from "usable" to "willing to use" domestic GPU platforms hinges on improving developer experience and reducing migration costs [12] - The engineering challenges of building large-scale systems without proprietary interconnects are highlighted, with a focus on achieving reliable low-latency communication and operational efficiency [14]