Core Insights - Morgan Stanley's report compares the operational costs and profit margins of various AI solutions in inference workloads, highlighting that most multi-chip AI inference "factories" have profit margins exceeding 50%, with NVIDIA leading the pack [1][3]. Profit Margins - Among selected 100 MW AI "factories," NVIDIA's GB200 NVL72 "Blackwell" GPU platform achieved the highest profit margin of 77.6%, translating to an estimated profit of approximately $3.5 billion [3]. - Google's self-developed TPU v6e pod ranked second with a profit margin of 74.9%, while AWS's Trn2 UltraServer and Huawei's Ascend CloudMatrix 384 platform reported profit margins of 62.5% and 47.9%, respectively [3]. Performance of AMD - AMD's performance in AI inference is notably poor, with its latest MI355X platform showing a profit margin of -28.2%, and the older MI300X platform at a significantly lower -64.0% [4]. Revenue Generation - NVIDIA's GB200 NVL72 chip generates $7.5 per hour, while the HGX H200 chip produces $3.7 per hour. Huawei's Ascend CloudMatrix 384 platform generates $1.9 per hour, and AMD's MI355X platform only generates $1.7 per hour [4]. - Most other chips generate revenue between $0.5 and $2.0 per hour [4].

Key Takeaways AMD is expected to post strong Q2 gains from data center and client segment revenue growth.Data center growth is fueled by MI300 AI chips and rising demand from major cloud partners.Embedded revenues are forecasted to decline 4.9% year over year due to industrial market softness.Advanced Micro Devices (AMD) is expected to have benefited from strong Data Center revenues in the second quarter of 2025. The company’s second-quarter results are expected to be released on Aug. 5.AMD benefits from a ...

Hi, I'm Vik Malyala, President and Managing Director for Supermicro EMEA. We are here at MWC. I'm super excited to present what we are doing together with AMD in bringing the most advanced and energy efficient solutions for our customers, whether they are focusing on training, inferencing, edge, or telco, whatever it may be, how we are actually bringing the value together.What we have here is the liquid-cooled systems, focusing on AI, primarily on training, as well as inferencing for people who are wanting ...

Core Viewpoint - The article discusses the advancements and competitive landscape in the semiconductor industry, particularly focusing on the latest chip technologies from major players like NVIDIA, Intel, AMD, and various domestic manufacturers in China [1][3]. Group 1: Major Chip Manufacturers - NVIDIA has introduced several high-performance chips, including the H100-SXM with 80 billion transistors and a transistor density of 98 million/mm², and the upcoming H200 series [5][6]. - Intel is set to release the Gaudi2 and Gaudi3 chips, with Gaudi3 featuring a 5nm process technology [6][8]. - AMD's MI300 series, including MI300X and MI300A, showcases significant transistor counts of 1.53 billion and 1.46 billion respectively, with MI300X having a transistor density of 15 million/mm² [5][7]. Group 2: Domestic Chip Developments - Chinese manufacturers are also making strides, with chips like the MLU370-X4 featuring 39 billion transistors and a 7nm process technology [5][6]. - The article highlights various domestic chips, including the MLU290-M5 and MLU270 series, which are designed for specific applications and show competitive specifications [6][8]. - The development of specialized chips, such as the 推理专用芯片 (Inference Dedicated Chips), indicates a growing focus on tailored solutions within the domestic market [9]. Group 3: Performance Metrics - The article provides detailed performance metrics for various chips, including power consumption and arithmetic intensity, with NVIDIA's GB200 achieving an arithmetic intensity of 2500 BF16 [7][8]. - The efficiency of these chips is highlighted, with some achieving significant performance per watt, indicating advancements in energy efficiency alongside processing power [7][8]. - The memory bandwidth and capacity of these chips are also discussed, with NVIDIA's H200-SXM featuring a memory bandwidth of 4.8 TB/s, showcasing the high-performance capabilities of modern chips [8][9].

Group 1 - OpenAI's CEO Sam Altman announced the adoption of AMD's MI300X and MI450 AI chips for their operations [1]

Advanced Micro Devices (AMD -2.35%) supplies some of the best chips in the world for computers, cars, game consoles, and data centers. The company's data center business is a key focus for investors right now, as demand soars for its graphics processing units (GPUs), which are designed for artificial intelligence (AI) development.AMD, as its known, is still chasing Nvidia in the AI data center market, but the company's latest GPUs could help close the gap. Plus, AMD is already a leading supplier of AI chips ...