AMD Advanced Micro Devices, Inc.BATS:AMDShavyfxhubAMD technical information. the rejection on the supply roof of the weekly ascending trendline could lead to strong correction and take profit after the massive bubble rally into 202.76 and my target is the 50% of the Fibonacci level which is around 150.20-149.879 AMD FUNDAMENTAL AMD and OpenAI finalized a landmark multi-year agreement for OpenAI to deploy up to 6 gigawatts (GW) of AMD GPUs, starting with an initial 1 GW rollout of the AMD Instinct MI450 series in the second half of 2026. This partnership is significant for AMD’s growth in the AI semiconductor market and has several advantages: Key Advantages of the AMD-OpenAI Deal: Massive Scale Deployment: The 6 GW commitment positions AMD as a core AI hardware provider for OpenAI’s next-generation AI infrastructure, significantly expanding its presence in high-performance computing for AI workloads. Multi-Generational Collaboration: The deal builds on prior cooperation with OpenAI using MI300X and MI350X GPUs, deepening AMD’s involvement over multiple future AI hardware generations. Financial Incentives: OpenAI holds warrants to buy up to a 10% stake in AMD stock tied to deployment milestones, aligning financial interests and incentivizing long-term collaboration. Strategic Market Credibility: Partnering with a leading AI research organization like OpenAI validates AMD’s technology and competitive positioning against rivals like NVIDIA in the generative AI chip market, which is forecasted to exceed $150 billion in value. Revenue Growth Catalyst: This deal could generate tens of billions in AI revenue over time, fueling AMD’s expansion into the rapidly growing AI data center sector. Ecosystem Synergy: OpenAI’s use of AMD hardware fosters optimized AI model development on AMD platforms, improving software-hardware integration and performance. AMD’s Q3 2025 revenue hit a record $9.2 billion, up 36% YoY, exceeding expectations. Strong sequential growth is expected in Q4 2025, with guidance around $9.6 billion driven by AI data center GPUs (MI350 series) and Ryzen client processors. The company foresees its AI data center business scaling to tens of billions in annual revenue by 2027 as adoption expands among hyperscalers, sovereign AI programs, and cloud providers. Key product launches on the horizon include the MI400 GPU family and next-generation EPYC server CPUs. AMD also emphasizes broadening its AI software ecosystem with ROCm 7 and partnerships with OpenAI and others. Business Model: AMD designs and sells high-performance microprocessors (CPUs), graphics processing units (GPUs), and adaptive computing chips, often licensing IP to OEMs and cloud providers. Key revenue drivers are client (PCs and gaming consoles), enterprise/data center (servers, AI accelerators), and embedded markets. The company leverages R&D for cutting-edge chips optimized for AI, cloud, gaming, and edge applications. AMD works closely with partners and customers to integrate hardware and software solutions (e.g., AI ecosystems, accelerated computing). Recent Acquisitions to Fuel Growth: Xilinx (2022, $49 billion): Expanded AMD’s portfolio into FPGAs, adaptive computing for telecom, automotive, cloud data centers, and industrial use cases. Post-acquisition, AMD integrated Xilinx’s AI engine technology into its Ryzen AI and planned EPYC CPU lines. Other smaller acquisitions include teams and tech from ZT Systems, Brium, Lamini, which bolster AI hardware and software capabilities. AMD's MI300X and M1450X GPUs are considered better than NVIDIA's H100 in several key areas, especially for AI workloads: Why MI300X and M1450X are Better: Memory Bandwidth and Capacity: The MI300X offers about 60% more memory bandwidth (5.3 TB/s) and more than double the memory capacity (192 GB HBM3) compared to NVIDIA’s H100 (80 GB HBM2e with 3.35 TB/s bandwidth). This higher bandwidth and capacity enable better handling of large AI models and data sets. Compute Performance: MI300X achieves peak FP16 performance of approximately 1.31 petaflops, outperforming H100's 0.99 petaflops. Benchmarks show the MI300X can deliver up to 5x faster instruction throughput and consistently 40%-60% better performance on AI inference latency with large models like LLaMA2-70B. Caching Architecture: AMD's CDNA 3 architecture in MI300X includes a massive Infinity Cache (256MB L3 cache), providing 3.5x greater bandwidth in L2 caching and 1.6x in L1 compared to H100. This improves efficiency in data access during computations. Scalability and Multi-GPU Performance: Early tests indicate the MI300X scales better in multi-GPU deployments, offering up to 60% higher peak system output throughput over NVIDIA setups. Software Ecosystem Growth: AMD’s ROCm software platform and AI optimization tools are rapidly maturing, improving real-world application performance for MI300X series GPUs. Caveats: NVIDIA's H100 has lower memory latency (57% less), which can benefit some workloads. H100 maintains advantages in some specific tensor operations and smaller batch sizes. NVIDIA’s ecosystem and software optimizations (including updates) remain strong competitive factors. Summary AMD's MI300X and M1450X excel over NVIDIA H100 mainly due to higher memory bandwidth and capacity, superior caching, and stronger compute throughput in large AI workload benchmarks. This makes them highly competitive leaders in AI data center GPUs, especially for large model Strategic acquisitions like Xilinx broaden product offerings and accelerate AI ecosystem development, positioning AMD as a major AI and adaptive computing player. #AMD #STOCKS