Core Viewpoint - The global AI chip market is becoming increasingly competitive, with Huawei's Ascend 910C GPU facing significant challenges in gaining traction against NVIDIA's entrenched ecosystem and products [1][2]. Group 1: Challenges Faced by Huawei - The entrenched CUDA ecosystem of NVIDIA poses a major barrier, as many Chinese tech companies have invested heavily in it, making it difficult for them to switch to Huawei's alternatives [1][2]. - Intense competition among Chinese tech companies leads to reluctance in adopting a competitor's product, further complicating Huawei's market penetration efforts [2]. - The Ascend 910C chip suffers from overheating issues, which negatively impacts its reliability perception in high-performance computing and AI training scenarios [2][3]. - Many Chinese tech companies have substantial NVIDIA GPU inventories, reducing their incentive to switch to Huawei's offerings in the short term [3]. - U.S. export controls create additional hurdles, as companies must carefully consider compliance risks when adopting Huawei chips, especially those with significant overseas operations [3]. Group 2: Technical Specifications and Market Position - The Ascend 910C chip reportedly offers 800 TFLOP/s of computing power with FP16 precision and up to 3.2 TB/s memory bandwidth, comparable to NVIDIA's H100 GPU [3]. - Huawei has introduced the "CloudMatrix 384," which bundles up to 384 Ascend chips to provide substantial computing power, although it lacks direct support for FP8 memory optimization, which is crucial for large-scale AI training [4][5]. - In contrast, NVIDIA continues to perform strongly in the AI infrastructure market, with significant visibility in business pipelines and projected revenues of approximately $400 billion to $500 billion per year from AI infrastructure projects [5]. - NVIDIA holds a dominant position in the AIB GPU market, with a remarkable 92% market share, further solidifying its leadership in the AI chip sector [5].