Performance Comparison - AMD EPYC 9575F CPU achieves approximately 1.24x higher total token throughput performance on Mixtral 8x7B compared to Intel Xeon 8592+ [1] - AMD EPYC 9575F CPU demonstrates roughly 1.10x greater total token throughput performance on Llama4-Maverick-17B-128E-FP8 versus Intel Xeon 8592+ [1] - AMD EPYC 9575F CPU exhibits about 1.05x improved AI inference throughput performance on Deepseek-R1-SGLang when compared to Intel Xeon 8592+ [1] - Both AMD EPYC 9575F and Intel Xeon 8592+ were tested with 8x AMD Instinct MI300X GPUs [1] Product & Technology - AMD EPYC 9575F is positioned as the highest performance CPU for hosting AI accelerators [1] Legal & Trademark - ©2025 Advanced Micro Devices, Inc [1] - AMD and the AMD Arrow Logo are trademarks of Advanced Micro Devices, Inc in the United States and other jurisdictions [1]

Core Viewpoint - Intel is scaling back its efforts in the AI accelerator market, particularly in AI training, as it acknowledges the dominance of Nvidia and shifts focus towards AI inference and emerging opportunities in agentic AI [1][2][6][11] AI Training Market - Intel has abandoned its Gaudi line of AI chips due to immature software and an unfamiliar architecture, leading to the cancellation of Falcon Shores, which was intended to succeed Gaudi 3 [1] - CEO Lip-Bu Tan stated that it is "too late" for Intel to catch up in the AI training market, recognizing Nvidia's strong market position [2][11] AI Inference Market - AI inference, which utilizes trained models, is seen as a potentially larger market than AI training, with companies like Cloudflare predicting its growth [6] - Intel plans to focus on AI inference and agentic AI, which are emerging areas with significant potential [7][11] Market Opportunities - There is a growing trend towards smaller, more efficient AI models that can run on less expensive hardware, presenting a market opportunity for Intel [9] - Intel could still succeed in AI chips for edge data centers and devices designed to run fully trained AI models [8] Rack-Scale AI Solutions - It remains uncertain whether Intel will continue developing rack-scale AI solutions, as the future of Jaguar Shores is unclear following Tan's statements [10]

Investment Rating - The report maintains an "Overweight" (OW) rating on Naura, AMEC, and ACMR, with revised target prices reflecting positive outlooks for these companies [6][37][55]. Core Insights - The outlook for China's wafer fab equipment (WFE) market remains strong, driven by better-than-expected demand from logic foundries and ongoing localization efforts [1][2]. - The total addressable market (TAM) forecast for China WFE has been raised from $36.6 billion (down 12% year-over-year) to $40.3 billion (down 3% year-over-year) for 2025, and from $35.1 billion (down 4% year-over-year) to $36.2 billion (down 10% year-over-year) for 2026 [3][9]. - China is expected to continue gaining market share in WFE, with approximately 25% of foundry capital expenditures allocated to domestic WFE in 2025, up from 20% in 2024 [4]. Market Demand and Supply Dynamics - Strong demand for logic foundries in China is anticipated in the second half of 2025, with expectations of increased spending related to AI applications [2][9]. - Despite concerns regarding oversupply in mature nodes, the report suggests that government initiatives may prioritize localization over economic rationale in the second half of 2025 [5]. - The report indicates that imports of semiconductor equipment into China may recover starting in July 2025, following a decline in early 2025 [21]. Company-Specific Developments - Naura has expanded its product portfolio, launching new ion implant equipment, and is expected to benefit from the increasing localization of semiconductor manufacturing in China [4][37]. - The report highlights that leading Chinese WFE players are likely to capture larger shares of the market due to their expanding product pipelines and advanced R&D capabilities [6][37]. - Naura's revenue growth is projected to be supported by increased capital expenditures from logic foundry and memory customers in 2025 [37][51]. Financial Projections - The report revises Naura's earnings estimates upward for 2025-2027, reflecting strong demand and market share gains [51][52]. - Naura's net sales are projected to increase from Rmb 41.88 billion in 2025 to Rmb 61.42 billion by 2027, with corresponding net income growth [63][66].

Core Insights - Nvidia reported a strong fiscal first-quarter earnings with a sales growth of 69% driven by demand for GPUs in artificial intelligence applications [3][4] - The company anticipates $45 billion in chip sales for the July quarter, but U.S. export controls on its H20 chip are expected to result in a loss of approximately $8 billion in potential sales [4][5] - Nvidia's CEO highlighted that China represents a $50 billion market that is currently inaccessible due to U.S. restrictions, which he believes are misguided and could push Chinese developers towards local alternatives [5][6] Sales and Market Dynamics - Nvidia's data center revenue reached $39.1 billion, with cloud providers accounting for about half of this revenue [9] - The latest Blackwell chips comprised 70% of Nvidia's data center sales, with significant deployments already made by major cloud providers like Microsoft [10][11] - The company is preparing to launch Blackwell Ultra, an upgraded version of its chip, which is expected to enhance performance and memory [11] Future Outlook and AI Demand - Nvidia is shifting focus from training AI models to inference, which is generating new demand for its GPUs as AI models require significantly more computing power [12][13] - The CEO noted a sharp increase in inference demand, with major companies like OpenAI, Microsoft, and Google experiencing substantial growth in token generation [14] - Nvidia's latest chips are designed to meet the increasing computational needs of modern AI models, which require extensive processing capabilities [13][14] Strategic Concerns - The CEO expressed concerns about the impact of U.S. export controls on Nvidia's business, emphasizing the importance of global technology leadership in the AI sector [16][17] - He indicated that the AI race extends beyond chip production to the overall technology stack, which includes advancements in 6G and quantum computing [17]

Core Insights - Supermicro has begun taking orders for enterprise AI systems featuring NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, enhancing performance for various AI workloads [1][2][3] - The systems are designed to support AI inference, development, generative AI, and other applications across multiple industries [1][6] - Supermicro's collaboration with NVIDIA aims to accelerate the deployment of on-premises AI solutions through validated designs and full-stack integrations [2][3] Company Offerings - Supermicro offers over 100 accelerated computing servers compatible with NVIDIA PCIe GPUs, including the RTX PRO 6000 Blackwell [4] - The new MGX-based system, SYS-212GB-NR, features a single-socket architecture that supports up to 4 GPUs, targeting edge AI solutions [7][8] - The product lineup includes various system families such as 5U PCIe accelerated computing systems, MGX systems, and edge-optimized systems, catering to diverse workload requirements [9][10][11] Industry Impact - The introduction of AI factories is expected to enable enterprises to make data-driven decisions and adapt quickly to market changes [6] - Supermicro's systems are designed to reduce the number of servers needed for advanced AI applications, thereby lowering deployment costs [8] - The focus on edge AI solutions reflects a growing demand for AI inference capabilities closer to data sources, enhancing operational efficiency [6][8]

Investment Rating - The investment rating for SMIC is Equal-weight [7]. Core Insights - SMIC's 1Q25 revenue was US$2.25 billion, reflecting a 2% quarter-over-quarter (Q/Q) increase and a 28% year-over-year (Y/Y) increase, driven by a 15% Q/Q growth in shipments due to geopolitical concerns, rising demand from consumption subsidies, and restocking in industrial and automotive sectors [2][5]. - The guidance for 2Q25 indicates a revenue decline of 4-6% Q/Q and a gross margin (GM) of 18-20%, down 2.5-4.5 percentage points Q/Q, attributed to a decline in blended average selling price (ASP) due to yield issues and rising equipment depreciation [3][5]. - Management expects the pressure on blended ASP to persist until Q3, with new equipment debugging taking time [3][5]. Summary by Sections Financial Performance - 1Q25 GM was 22.5%, up 0.1 percentage points Q/Q, exceeding market expectations by 2.1 percentage points and 1.8 percentage points, driven by a utilization rate (UTR) of 89.6% [2]. - Revenue projections for the fiscal years ending in 2025, 2026, and 2027 are US$10.155 billion, US$11.620 billion, and US$12.505 billion respectively [7]. Market Dynamics - The strong demand for AI inference is expected to drive revenue growth for SMIC's advanced nodes, although GM erosion from yield decline may negatively impact earnings performance [5]. - Management noted that rush orders from US customers are being observed as they build inventory for 2025 and 2026, with limited financial impact on SMIC due to capacity constraints and logistics bottlenecks [9]. Capacity and Investment - SMIC plans to expand capacity at a rate of an additional 50 kilowatts per month (kwpm) per year, with 82-85% of the US$7.5 billion capital expenditure in 2025 allocated for equipment purchases [9]. - R&D expenses are expected to account for 8-10% of revenue in the long run, despite a temporary reduction in Q1 due to rush orders occupying capacity [9].

Industry Overview - The AI industry is facing an uncertain macroeconomic environment, with signs indicating a potential cooling in demand for AI infrastructure [1] - Super Micro Computer has reduced its guidance due to delayed purchasing decisions from customers, and some tech giants are scaling back on data center expansions [1] Investment Focus - Investors are still interested in AI, with a recommendation to avoid AI hardware companies like Super Micro and Nvidia, as well as hyperscalers like Microsoft [2] - The focus should be on companies specializing in AI inference and efficient, specialized AI models, with IBM and Cloudflare highlighted as top picks [2] IBM's AI Strategy - IBM has secured $6 billion in generative AI-related business, with $1 billion added in the first quarter, primarily from its consulting business [3] - The Watsonx AI platform is central to IBM's AI efforts, enabling enterprises to build, test, deploy, and manage AI models, with potential cost reductions of up to 98.5% by using specialized models [4] - IBM's upcoming z17 mainframe, launching in June, can perform 450 billion AI inferencing operations daily, making it suitable for real-time tasks like credit card fraud detection [6] Cloudflare's AI Capabilities - Cloudflare focuses on speed, allowing developers to perform fast computations on user requests, covering various use cases including AI inference tasks [8] - The platform supports over 50 open-source AI models and integrates with Cloudflare Workers for programmatic access [9] - By focusing on AI inference with smaller models, Cloudflare can utilize older, less expensive AI accelerators, reducing costs while maintaining performance [10] - Cloudflare's revenue grew by 27% year over year in Q4 2024, with a record number of large customers spending over $1 million annually [11]

Core Insights - Silicon Motion Technology Corporation reported a decrease in net sales for Q1 2025, with GAAP net sales at $166.5 million, down 13% quarter-over-quarter and 12% year-over-year [3][7] - The company experienced a decline in both GAAP and non-GAAP net income, with GAAP net income at $19.5 million ($0.58 per diluted ADS) and non-GAAP net income at $20.3 million ($0.60 per diluted ADS) [4][6] - Despite the challenging macro environment, the company noted strong demand for its PCIe Gen 5 controller, driven by AI inference needs and a rebound in the smartphone market [5][11] Financial Highlights - Q1 2025 GAAP net sales: $166.5 million, down from $191.2 million in Q4 2024 [3][6] - GAAP gross margin improved to 47.1% from 45.8% in Q4 2024, while operating margin decreased to 5.9% from 9.3% [6][24] - Non-GAAP operating profit for Q1 2025 was $14.9 million, with a non-GAAP operating margin of 8.9% [6][27] Sales Performance - SSD controller sales decreased by 10% to 15% quarter-over-quarter and 20% to 25% year-over-year [7] - eMMC and UFS controller sales saw a decline of 15% to 20% quarter-over-quarter but only 0% to 5% year-over-year [7] - SSD solutions sales dropped by 20% to 25% quarter-over-quarter and 35% to 40% year-over-year [7] Shareholder Returns - The company announced a new $50 million share repurchase program, with $24.3 million repurchased in Q1 2025 at an average price of $56.96 per ADS [10][11] Business Outlook - The company anticipates revenue growth driven by new product introductions, including an 8-channel PCIe Gen 5 controller and UFS 4.1 controllers, expected to ramp up in the second half of 2025 [11] - Management projects Q2 2025 revenue to be between $175 million and $183 million, representing a quarter-over-quarter increase of 5% to 10% [11][12]

The most powerful generative AI models from the likes of OpenAI, Alphabet, and Anthropic require costly and power-hungry AI accelerators stuffed into data centers to produce results. OpenAI's recent GPT-4.5 model, for example, was rolled out in phases to users because it required an immense amount of computational resources.AI models from Chinese start-up DeepSeek released earlier this year turned some assumptions about the AI infrastructure market on their heads. DeepSeek managed to produce a model that wa ...

Summary of SMIC Conference Call Company Overview - **Company**: Semiconductor Manufacturing International Corporation (SMIC) - **Ticker**: 0981.HK - **Market Cap**: US$35,491 million - **Current Price**: HK$39.15 - **Price Target**: HK$40.00 - **Rating Change**: Upgraded from Underweight (UW) to Equal-weight (EW) [1][5][42] Key Industry Insights - **AI Chip Demand**: Domestic demand for AI GPUs is larger than expected, driven by rising AI inference needs and limited supply from US AI GPUs [2][9] - **Local Chip Production**: SMIC is expected to be a key supporter for local AI chip designers due to the surge in demand for domestic chips [2][39] - **Capacity Constraints**: SMIC's advanced node capacity is limited by equipment bottlenecks, particularly in lithography and inspection tools [3][18] Financial Performance and Projections - **Revenue Growth**: Projected revenue for 2025 is US$10,155 million, reflecting a 3% increase from previous estimates [39][40] - **Earnings Estimates**: EPS estimates for 2025 have been raised to US$0.158, a 5% increase from prior estimates [39][40] - **Gross Margin**: Expected to stabilize around 21.4% in 2025, with potential for expansion due to rising ASPs and improved yield rates [30][46] Production Capacity and Yield - **AI GPU Production**: SMIC could produce approximately 3.6 million units of AI GPUs annually, fulfilling domestic demand [4][19] - **Wafer Production**: Each 12-inch wafer can yield about 20 good dies of Huawei's 910B chip, with a yield rate of 30-35% [4][19] - **Advanced Node Capacity**: Forecasted capacity for 14nm/10nm/7nm FinFET nodes is expected to reach 50kwpm by the end of 2025 [3] Market Dynamics - **Pricing Power**: Concerns about oversupply in mature nodes may lead to intensified pricing competition in 2H25 [46][58] - **Investment in AI**: Chinese CSPs are expected to allocate up to RMB300 billion for AI capex, primarily for acquiring AI servers and GPUs [16][17] Risks and Considerations - **Potential Risks**: - Weaker-than-expected demand for AI chips - Capacity expansion limitations due to export controls - Low yield rates that may not improve [45][58] - **Valuation Concerns**: Current stock trading at +2 standard deviations of historical average P/B, indicating potential overvaluation [5][47] Conclusion - **Outlook**: SMIC is well-positioned to benefit from the localization of AI chip production and increasing domestic demand, but faces challenges related to capacity constraints and market competition. The upgrade to an Equal-weight rating reflects a cautious optimism about future growth prospects [1][42][58]