Core Insights - H20's resumption of sales to China is expected to alleviate supply pressure on computing chips, stimulating the entire computing infrastructure and AI industry chain [2][3] - Since the rebound on April 9, overseas computing has seen a significant increase of 40.9%, while domestic computing, represented by Huawei's chain, has only increased by 21.1% [3][4] - The performance of domestic computing has improved, and H20's impact on domestic computing is limited, indicating that domestic computing still has long-term growth potential [5] Industry Overview - The computing power industry chain has been catalyzed by H20's return to the Chinese market, which is designed to comply with U.S. export restrictions and is specifically tailored for the Chinese market [3][5] - The domestic computing power industry is entering a growth cycle, supported by technological advancements, commercial applications, and increasing demand for AI models [4] - Key companies in the domestic computing power sector, such as Huawei, have demonstrated significant performance improvements, with Huawei's computing cluster outperforming NVIDIA's GB200 NVL72 [4][5] Investment Opportunities - The report suggests focusing on specific segments within the computing infrastructure industry, including servers, liquid cooling, copper connections, PCBs, optical communications, cloud computing, and domestic computing [5] - The IPO acceptance of domestic GPU manufacturers like Muxi Integration and Moore Threads fills the gap in the A-share market for full-function GPUs, further supporting the domestic computing ecosystem [4]

Core Viewpoint - The A-share market is experiencing a "slow bull" trend, with the Shanghai Composite Index rising over 7% since early June, driven by significant changes in funding dynamics and a shift in market risk appetite [1][3]. Group 1: Market Dynamics - The financing balance surged by 26.5 billion yuan in the week of June 27, reaching a new high since February 2025, indicating a transition from a corrective rebound to a trend-driven market [1]. - The current market rally is characterized by a multi-dimensional funding structure, with contributions from financing funds, quantitative funds, and industrial capital, contrasting with the previous dominance of northbound funds [3]. Group 2: Sector Analysis - The market's trading focus in July revolves around "anti-involution" and infrastructure, with the former addressing supply-side reforms in overcapacity industries like coal and cement, and the latter focusing on major strategic projects [4]. - The anti-involution sector is seeing intensified policy actions, such as the National Energy Administration's inspection of coal mine production, which has led to significant gains in the coal sector [4]. - The infrastructure sector is primarily centered on the Yajiang Hydropower Project, which has a long construction cycle of 10-15 years, suggesting a medium to long-term investment perspective [5]. Group 3: Technology Sector Opportunities - Despite a temporary lull in the technology sector, the current market conditions are creating significant opportunities due to a decrease in funding congestion and ongoing industrial advancements [5][7]. - The semiconductor sector is poised for a value reassessment, with the STAR 50 Index remaining stagnant while companies like SMIC and Huawei are making technological strides [8][9]. - The AI sector is expected to see a 20-30% increase in domestic AI server shipments due to the release of the H20 chip, with strong visibility in orders for companies like Inspur and Zhongke Shuguang [11]. - The robotics sector is advancing through a structured approach, with significant market growth projected, particularly in humanoid robots, which are expected to reach a market size of 870 billion yuan by 2030 [11]. Group 4: Investment Outlook - The current market is primarily trading on anti-involution and infrastructure narratives, which are more medium to long-term in nature. As volatility occurs, funds may shift, making the technology sector, with its lower funding congestion and strong industrial narrative, a preferred focus for future investments [12].

Core Viewpoint - Nvidia's founder Jensen Huang is making significant efforts to regain market share in China's AI computing sector after losing ground to domestic chip companies during the U.S. export restrictions [4][5][8]. Group 1: Nvidia's Market Strategy - Jensen Huang's visit to China includes meetings with government officials and key industry players, aiming to restore confidence in Nvidia's operations in the region [4][5]. - Nvidia has received assurances from the U.S. government to resume sales of the H20 chip in China, which is a downgraded version of the H100 series designed to comply with export regulations [5][11]. - The company's market share in China has dropped from 95% during the export control period in 2022 to 50% due to the emergence of local competitors [8]. Group 2: Domestic Competitors - Chinese chip manufacturers have rapidly developed alternatives to Nvidia's H20 chip, including products from Kunlun, Moore Threads, Huawei, and Cambricon, which are aggressively targeting Nvidia's market share [7][12]. - Domestic chip companies have reported significant demand, with some experiencing a surge in orders and achieving substantial revenue growth, such as Cambricon's quarterly revenue increasing by 42.3 times [12][13]. - The competitive landscape is shifting as local firms focus on AI inference capabilities, which are less complex than training models, allowing them to better compete against Nvidia [14][15]. Group 3: Financial Implications - Nvidia's revenue loss due to the H20 ban is projected to be around $8 billion (approximately 57.3 billion yuan) in Q2 2025 [17]. - China represents a crucial market for Nvidia, contributing about 15% of its global revenue, equating to approximately $18 billion annually [16]. - The ongoing geopolitical tensions and export restrictions have created uncertainty for Nvidia's long-term prospects in China, despite the potential for short-term sales recovery with the H20's return [19][20].

Core Insights - The report highlights the sustained high demand for domestic computing power driven by ongoing U.S. restrictions on advanced chip imports, accelerating the domestic substitution process [3][7] - Domestic cloud service providers are increasing capital expenditures, gradually releasing industrial demand, while the iteration of domestic AI large models and applications is further boosting computing power needs [3][7] Industry Performance - The report provides a snapshot of market indices, with the Shanghai Composite Index closing at 3454.79, down 0.09%, and the Shenzhen Component Index at 10412.63, down 0.61% [4] - The performance of various sectors is noted, with steel up 3.37% and electronics down 2.01% [5] Key Focus Areas - The domestic computing power market is experiencing a boom, with Huawei's Ascend 910C servers being deployed in significant quantities, indicating a new phase in domestic computing commercialization [7] - The Ascend 910C chip boasts a single-chip computing power of 320 TFLOPS (FP16), designed for efficiency and low power consumption, suitable for AI tasks [7] - Major domestic internet companies are ramping up investments in AI infrastructure, with Alibaba planning to invest 380 billion RMB over three years, and Tencent's capital expenditure reaching 275 billion RMB in Q1 2025, up 91% year-on-year [8] Demand Drivers - The report notes that application-side inference is expected to drive demand growth, with significant increases in token usage reported by major companies like Alphabet and ByteDance [9] - The domestic supply side, including chips and supernode deployments, has achieved technological breakthroughs, which will lead to increased demand for computing power as industry applications evolve [9]

Core Viewpoint - The article discusses the recent regulations issued by the U.S. Department of Commerce, which impose restrictions on the use of Huawei's Ascend AI chips globally, highlighting the implications for companies using these advanced computing chips [1][3]. Summary by Sections U.S. Regulations on Huawei Chips - The U.S. Department of Commerce has stated that using Huawei's Ascend chips anywhere in the world violates U.S. export control regulations [3]. - Specific models mentioned include the Huawei Ascend 910B, 910C, and 910D, which may lead to penalties for companies that utilize them [3]. Classification of High-Performance Chips - The regulations categorize advanced high-performance chips into three classes based on their total processing performance (TPP) and performance density: 1. Chips with TPP greater than or equal to 4800 TOPS, or TPP greater than or equal to 1600 TOPS with a performance density of 5.92 or higher [4]. 2. Chips with TPP between 2400 TOPS and 4800 TOPS, and performance density between 1.6 and 5.92, or TPP above 1600 TOPS with performance density between 3.2 and 5.92 [4]. 3. High Bandwidth Memory (HBM) components with memory bandwidth density greater than 2 GB/s per square millimeter [5]. Consequences of Non-Compliance - The regulations indicate that violations could result in severe penalties, including up to 20 years of imprisonment [6]. - Experts have commented that these guidelines are quite stringent, effectively forcing companies to choose between Huawei's H chips and NVIDIA's N chips [6].

Core Insights - The next-generation AI model DeepSeek-R2 is set to be released, featuring advanced parameters and architecture [1][5] - DeepSeek-R2 will utilize a hybrid expert model (MoE) with an intelligent gating network, significantly enhancing performance for high-load inference tasks [5] - The total parameter count for DeepSeek-R2 is expected to reach 1.2 trillion, doubling the 671 billion parameters of DeepSeek-R1, making it comparable to GPT-4 Turbo and Google's Gemini 2.0 Pro [5] Cost Efficiency - DeepSeek-R2's unit inference cost is projected to decrease by 97.4% compared to GPT-4, costing approximately $0.07 per million tokens, while GPT-4 costs $0.27 per million tokens [8] - The model's cost efficiency is attributed to the use of Huawei's Ascend 910B chip cluster, which achieves a computational performance of 512 PetaFLOPS with an 82% resource utilization rate [7][8] Hardware and Infrastructure - DeepSeek-R2's training framework is based on Huawei's Ascend 910B chip cluster, which has been validated to deliver 91% of the performance of NVIDIA's previous A100 training cluster [7] - The introduction of Huawei's Ascend 910C chip, which is entering mass production, may provide a domestic alternative to NVIDIA's high-end AI chips, enhancing hardware autonomy in China's AI sector [10]