Investment Rating - The report assigns a positive outlook for MediaTek, indicating a potential for growth in the upcoming quarters, particularly in the AI and mobile sectors [2][3]. Core Insights - MediaTek's Q1 2025 revenue reached NT$153.3 billion, showing a quarter-over-quarter increase of 11.1% and a year-over-year increase of 14.9%. Operating profit was NT$30.1 billion, with a net profit of NT$29.5 billion [2][7]. - The demand recovery in mainstream and entry-level markets has driven growth in the mobile business, with expectations for further market share and average selling price (ASP) increases with the upcoming flagship SoC launch [2][14]. - MediaTek is collaborating with NVIDIA to target the AI ASIC market, projecting AI ASIC revenue to reach $1 billion by 2026 [3][28]. Summary by Sections Overall Performance - In Q1 2025, MediaTek achieved a revenue of NT$153.3 billion, with operating profit at NT$30.1 billion and net profit at NT$29.5 billion. The gross margin was 48.1%, reflecting a slight decline from the previous quarter and year [7][14]. Business Segmentation - **Mobile Business**: Contributed 56% to total revenue, with a 6% increase year-over-year and quarter-over-quarter, driven by demand recovery in mainstream and entry-level markets [14]. - **Intelligent Edge Platform**: Accounted for 39% of total revenue, showing a 32% year-over-year and 23% quarter-over-quarter increase, benefiting from upgrades in connectivity technology and AI applications [15]. - **Power IC Business**: Made up 5% of total revenue, with a 7% year-over-year increase but a 9% quarter-over-quarter decline [16]. Performance Guidance - For Q2 2025, MediaTek expects revenue to be between NT$147.2 billion and NT$159.4 billion, with a projected gross margin of 47% (±1.5 percentage points) [17][18].

Core Viewpoint - Apple's decision to purchase approximately $1 billion worth of NVIDIA's GB300 NVL72 GPU cluster servers marks a significant shift in its AI strategy, acknowledging the advantages of the GPU ecosystem and generative AI paradigm over its self-developed chips [1][3][21]. Group 1: Apple's Shift to NVIDIA - Apple has historically relied on its self-developed chips, achieving great success with its Apple Silicon series in mobile and edge computing [3]. - The recent order for NVIDIA's GPUs indicates Apple's recognition of the GPU ecosystem's superiority in the generative AI space, driven by urgent market demands for high-performance computing [3][4]. - Analysts suggest that Apple plans to order around 250 NVL72 servers, with each server costing between $3.7 million and $4 million, totaling nearly $1 billion [3]. Group 2: Implications of Siri's Performance - Siri's declining competitiveness against rivals like Google Assistant and Alexa has prompted Apple to reassess its AI hardware strategy [4][5]. - The anticipated updates to Siri have been delayed, reflecting the challenges Apple faces in enhancing its AI capabilities [4][5]. Group 3: Generative AI and Market Dynamics - The rise of generative AI has redefined user expectations for intelligent assistants, shifting from simple command execution to intelligent collaboration [5]. - Apple's investment in NVIDIA GPUs is speculated to support the development of an Apple LLM, enhance Siri, and integrate AI into various applications [5][6]. Group 4: GPU vs. ASIC - The choice of NVIDIA's GPUs over self-developed ASICs highlights the critical importance of time and performance in the AI race, with NVIDIA's established ecosystem providing immediate solutions [8][16]. - NVIDIA's GPUs have become the de facto standard for training large language models (LLMs), showcasing their performance and ecosystem maturity [8][11]. - The high cost of NVIDIA GPUs, which have surged to $90,000 each, reflects their dominant market position, with NVIDIA reporting a revenue of $39.3 billion and a gross margin exceeding 70% [8][9]. Group 5: Future Outlook - Despite the current preference for NVIDIA GPUs, Apple may still pursue a hybrid strategy, utilizing NVIDIA for model training while relying on its own chips for inference [6][19]. - The ongoing competition between ASICs and GPUs suggests that while ASICs may face challenges now, they are not entirely out of the picture for future applications [19][21].