壁仞科技向港交所递交上市申请的动作，不仅是这家国产GPU龙头的资本进阶，更被视作中国自主算力突破的重要信号。作为第五大股东的上海临港， 其"基金+基地"的深度绑定模式，也让市场看到了国产硬科技成长背后产融协同的力量。 商业化落地的加速推进，让技术价值逐步转化为市场竞争力。在政策与市场的双重驱动下，壁仞科技已实现三大运营商的全面覆盖，其壁砺系列产品在中 国电信千卡集群落地应用，并参与浙江乌镇智算中心等重大项目建设。针对不同场景需求，壁仞形成了清晰的产品矩阵：BR100主攻AI训练与科学计算， 壁砺110E推理卡则以1.3倍于主流方案的算力密度和70%的能耗节省，在文生图、语音识别等推理场景快速渗透。渠道布局上，通过超讯通信担任行业总 代，2025年已设定2万颗芯片的进货目标，同时与科华数据联合开发大模型一体机，拓宽政企市场触达路径。不过营收规模仍显稚嫩，2025年营收约2.8亿 元，与摩尔线程18亿元的营收相比存在差距，如何将技术优势转化为盈利能力，将是上市后亟待解决的课题。 从技术突破到生态成型，再到商业落地，壁仞科技的成长轨迹勾勒出国产GPU的突围路径。港股上市带来的资本注入，或将加速其在封装国产化、生态扩 ...

Group 1 - The article highlights the support from the Ministry of Industry and Information Technology for domestic GPU development, indicating a competitive landscape among local companies in the GPU sector [1] - Moores Threads is developing the MTT S80, a full-featured GPU capable of running major games, with a Pre-IPO valuation of 25.5 billion [1] - Jingjia Micro is positioned as a key player with its JM9 GPU nearing the performance of GTX 1050, and a significant market share in government and financial sectors [1] - Birran Technology's BR100 GPU boasts three times the computing power of international flagship products, positioning it as a leader in domestic alternatives despite being listed by the US [2] - Muxi Integration has successfully delivered the Xiyun C500 GPU, with plans for the C600 to support FP8 and CUDA compatibility, marking it as a major player in domestic scaling [3] - Lishuan Technology is set to launch a 6nm GPU in 2025 that will outperform RTX 4060, focusing on digital twins and out-of-order rendering [4] - Haiguang Information stands out as the only company with both CPU and GPU capabilities, forming a unique ecosystem with products widely used in various sectors [5] Group 2 - The article notes that while domestic GPUs may struggle to catch up with established players like NVIDIA, AMD, and Intel in the short term, there is potential for significant growth in the long term, similar to the evolution seen in the home appliance and automotive industries [5]

Core Insights - The global computing power landscape is evolving into two parallel paths, with domestic and international routes differing, and opportunities for domestic chips in inference scenarios are expected to emerge this year [1][4] - Two AI chip companies, Muxi Integrated Circuit (Shanghai) Co., Ltd. and Moore Threads Intelligent Technology (Beijing) Co., Ltd., are nearing their IPOs, with Muxi's counseling work completed and Moore Threads' status changing to acceptance [1][2] - The demand for AI chips in China is increasing, with several companies adapting to the popular DeepSeek-R1 model, leading to a significant shift in market dynamics [3][4] Company Summaries - Muxi and Moore Threads were founded in 2020, while Suiruan Technology and Birun Technology were established in 2018 and 2019, respectively; the latter two companies have slower IPO progress compared to the former [2] - Moore Threads has the highest valuation among the four companies at 25.5 billion yuan, followed by Suiruan Technology at 16 billion yuan, Birun Technology at 15.5 billion yuan, and Muxi at 10 billion yuan [2] - Founders of these companies have backgrounds in major overseas chip firms, with Moore Threads' CEO previously serving as NVIDIA's China General Manager and Muxi's founders coming from AMD [2] Market Dynamics - The demand for domestic AI chips has surged, with IDC reporting that 34.6% of the Chinese data center accelerator market was comprised of domestic solutions last year, and this figure is expected to exceed 40% in the first half of this year [3] - The DeepSeek application has driven significant demand for domestic computing power, with many companies adapting their products to this model [3][4] - The global computing power foundation is shifting, with 98% of large model training still relying on NVIDIA, but there is potential for a portion of pre-training to transition to non-NVIDIA cards by the end of the year [4]

Core Viewpoint - The article discusses the performance of domestic GPUs, highlighting the competitive landscape and the impact of sanctions on production capabilities. It emphasizes that while the BR100 from Birun is the most powerful, it cannot be mass-produced due to sanctions, leaving Huawei's 910C as the strongest available option [1][2]. Performance Comparison - The performance ranking of GPUs indicates that the Huawei 910C leads, followed by the Haiguang BW100, with the latter achieving approximately 87% of its potential performance. The Cambrian 590's performance is uncertain, potentially reaching 80% [2]. - The Haiguang BW100 has a deep computing capability of over 400T, which is about 50% of the H800's performance, while the 910C reaches approximately 60% of the H800's performance [1][2]. Memory and Bandwidth - Most domestic GPUs utilize HBM2e memory due to sanctions preventing the use of HBM3e. Sufficient memory is crucial for initiating inference tasks, as insufficient memory can hinder model startup [3]. - Huawei leads significantly in memory bandwidth, which is a critical factor for performance [4]. Pricing Insights - Current market prices for GPUs are as follows: Haiguang BW100 at approximately 100,000 yuan, Huawei 910B at around 70,000 yuan, and 910C at about 180,000 yuan. The Cambrian 590 has seen a price drop from 80,000-85,000 yuan to between 60,000-70,000 yuan [2]. Technical Specifications - A table summarizes key specifications of various GPUs, including memory type, bandwidth, capacity, and arithmetic intensity. For instance, the Huawei 910C features HBM2e with a bandwidth of 3.2 TB/s and a memory capacity of 64 GB [5].