{"title":"Supermicro SYS-221H-TNR Server GPU Upgrades","description":"\u003cdiv class=\"gpu-config\"\u003e\n  \u003cdiv class=\"config\"\u003e\n    \u003cdiv class=\"gpu-content\"\u003e\n    \u003ch3\u003eSupermicro SYS-221H-TNR GPU Configuration\u003c\/h3\u003e\n     \u003cp\u003e The Supermicro SYS-221H-TNR is a dual-processor GPU server designed for high density acceleration workloads, offering 4 PCIe 5.0 x16 dual-slot or 8 PCIe 5.0 x16 single-slot GPU cards for maximum compute expansion. The system provides abundant PCIe lanes and bandwidth to drive multiple enterprise-grade GPUs simultaneously, making it ideal for AI\/ML training, data analytics, rendering, and other GPU-accelerated business applications. The SYS-221H-TNR delivers the reliability, throughput, and scalability required for modern compute-intensive workflows in enterprise and datacenter environments. \u003c\/p\u003e\n    \u003ca href=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/sys-221h-tnr.pdf?v=1765378692\" target=\"_blank\"\u003eTechnical Guide\u003c\/a\u003e\n  \u003c\/div\u003e\n\n  \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/SYS-221H-TNR_main.jpg?v=1765378693\" alt=\"Supermicro SYS-221H-TNR GPU server\"\u003e\n  \u003c\/div\u003e  \n\u003c\/div\u003e\n\n\n\u003cdiv class=\"gpu-upg-tips page-width\"\u003e\n  \u003ch3\u003eCloud Ninjas Supermicro SYS-221H-TNR GPU Upgrade Tips\u003c\/h3\u003e\n  \u003cul class=\"tip-list\"\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-squares.svg?v=1747162786\" alt=\" Supermicro SYS-221H-TNR GPU slots\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eThe total number of GPU slots for the Supermicro SYS-221H-TNR server is 4 for dual-slot or 8 for single-slot cards, dual-slot and single-slot cards will run at x16 links. It is important to ensure that the PCIe generation is identical to the generation supported by the CPU.\u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/network-card-64.png?v=1764109269\" alt=\" Supermicro SYS-221H-TNR GPU interface \"\u003e\n      \u003cspan class=\"box-cnt\"\u003eThe Supermicro SYS-221H-TNR server supports PCIe 5.0 slots for the GPU. PCIe 4.0 is supported due to backwards compatibility.\u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-octagon-alert.svg?v=1747165652\" alt=\" Supermicro SYS-221H-TNR GPU compatibility validation\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eEnsure your chassis supports full-length \/ full-height or double-wide GPUs if needed. Note that some servers only support passive-cooled (blower) data-center GPUs such as NVIDIA A100\/T4\/L40\/L40S\/H100 etc.\u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-shopping-bag.svg?v=1747165795\" alt=\" Supermicro SYS-221H-TNR GPU from Cloud Ninjas\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eBuy “Supermicro SYS-221H-TNR” GPUs today from Cloud Ninjas!\u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-octagon-alert.svg?v=1747165652\" alt=\" Supermicro SYS-221H-TNR system compatibility\"\u003e\n      \u003cspan class=\"box-cnt\"\u003e We recommend that you confirm the power supply and CPU and can support the newer GPU to avoid botlenecks or installation issues. The Supermicro SYS-221H-TNR has for GPU support, 2x Redundant 1200W 80 PLUS Titanium PSUs.  \u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e \n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-speed.svg?v=1747162786\" alt=\" Supermicro SYS-221H-TNR Memory Generations\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eThe memory generations supported by the Supermicro SYS-221H-TNR are, HBM3, HBM2 and GDDR6. \u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-shapes.svg?v=1747162786\" alt=\" Supermicro SYS-221H-TNR video modeling tips\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eUpgrade to NVIDIA GPUs built for real-time ray tracing and high-speed viewports to speed up rendering and design workflows in apps like Blender, Maya, SolidWorks, and AI content creation.\u003c\/span\u003e\n    \u003c\/li\u003e\n    \u003cli class=\"tipbox\"\u003e\n      \u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-speed.svg?v=1747162786\" alt=\" Supermicro SYS-221H-TNR VRAM Sizes\"\u003e\n      \u003cspan class=\"box-cnt\"\u003eThe Supermicro SYS-221H-TNR can support GPUs that range from 40GB of VRAM to 94GB of VRAM, keep in mind some GPUs have NVLink bridges as perform much better than non NVLink GPUs, hence the higher the VRAM the more performance you get on your AI GPU cluster.\u003c\/span\u003e\n    \u003c\/li\u003e\n  \u003c\/ul\u003e\n\u003c\/div\u003e\n\n\n\u003cdiv class=\"gpu-qa\"\u003e\n  \u003cdiv class=\"page-width\"\u003e\n    \u003ch3\u003eCloud Ninjas's Supermicro SYS-221H-TNR Q\u0026amp;A\u003c\/h3\u003e\n    \u003cdiv class=\"qanda\"\u003e\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e1. What are the benefits of upgrading to a enterprise NVIDIA GPU? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eUpgrading to a professional NVIDIA GPU improves performance, stability, and eficiency in AI, 3D design, video editing, and simulation workflows. Get your GPUs at \u003ca href=\"https:\/\/cloudninjas.com\/\"\u003ehttps:\/\/cloudninjas.com\/\u003c\/a\u003e.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e2. How do I know if I need a GPU upgrade? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eIf you are experiencing slow rendering times, or performance bottlenecks, it is a strong sign your GPU needs upgrading. When upgrading, it is strongly recommended to ensure the PCIe interface of your upgrade matches the interface on your system. It is also recommended to ensure the power supply will be compatible with the GPU, and GPUs in total should be under the total PSU power, do not forget to consider the CPU and other components for power consumption and choosing your GPU card.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e3. Which NVIDIA GPU is best for AI and machine learning?  \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eGPUs with strong Tensor core perfomance and high VRAM such as the NVIDIA RTX Pro and A-series deliver superior AI training and inference performance because they are specifically engineered to accelerate deep learning workloads. These GPUs combine advanced matrix-processing Tensor cores with fast GDDR6\/GDDR7 or HBM memory to maximize throughput, support larger AI models, enable higher batch sizes, and maintain scalable performance during long training sessions. As a result, NVIDIA enterprise GPUs provide faster neural network training, lower latency, and significantly improved scalability for machine learning, computer vision, and generative AI applications.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e4. How much VRAM do I need for professional workloads?   \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eMost AI, 3D, and simulation workloads run best with 16-24GB of VRAM or more, especially when working with large models or complex scenes.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e5. Will upgrading my GPU improve 4K or 8K video editing?   \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eYes. Modern GPUs with updated NVENC\/NVDEC encoders greatly improve editing, playback, and thermal requirements.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e6. What hardware do i need to check before upgrading my GPU?   \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eEnsure your power supply, cooling system, and case size can support the new GPU's power draw and thermal requirements. In order to see the most improvement from your upgrade, ensure the PCIe generations match on your GPU and your system's motherboard.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e7. Can an older CPU bottleneck a new GPU? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eYes. if your CPU is outdated, it may limit the performance of a newer GPU, especially in AI training and graphics heavy tasks.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e8. Are NVIDIA enterprise GPUs better for business software? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eYes. Professional NVIDIA GPUs are ISV-certified for applications like AutoCAD, SolidWorks, and Adobe, ensuring maximum performance and reliability. The NVIDIA GPUs are also ideal for softwares that run LLMs locally such as LM Studio or Abacus.AI. Learn more about ISV certifications\u003ca href=\"https:\/\/www.nvidia.com\/en-us\/products\/servers\/isv-certifications\/\"\u003e here\u003c\/a\u003e\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e9. Do GPU upgrades help with engineering simulations? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eHigh bandwidth, ECC enabled GPUs significantly speed up engineering and scientific simulations by providing fast, reliable memory access that reduces cmputation time and prevents data corruption. In applications like ANSYS, MATLAB, COMSOL, and other CAE tools, GPUs with high memory bandwidth and ECC VRAM deliver more accurate simulation results, faster parallel processing and greater numerical stability. This is especially true when running large finite-element models, multiphysics simulations, or data-intensive mathematical workloads. This combination of speed and reliability makes professional GPUs essential for engineers, researchers, and scientists who need consitstent performance and trustworthy results in their simulation environments.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e10. How often should businesses upgrade their GPUs? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eMost companies upgrade every 3-5 years to stay compatible with modern software and maintain competitive performance. It is recommended to have a yearly assessment for potential upgrades based on the business' AI workloads.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e11. What's the difference between consumer and professional NVIDIA GPUs? \u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eProfessional GPUs offer ECC memory, long term driver support, and certifications for engineering and design software. These features are critical for businesss reliability.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e12. Do I need multiple GPUs for AI or rendering?\u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eMulti GPU setups benefit heavy AI training, simulations, and large scale rendering. Many businesses see major gains from just one powerful upgrade.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e13. Will uprading my GPU reduce downtime?\u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eYes. Newer GPUs provide better stability, fewer crashes, and improved driver support, which helps keep workflows running smoothly.\u003c\/span\u003e\n        \u003c\/div\u003e\n\n        \u003cdiv class=\"q-list\"\u003e\n          \u003cspan class=\"question\"\u003e14. Do I need to update drivers after installing a new GPU?\u003cbutton type=\"button\" id=\"btn-open\"\u003e\u003cimg src=\"https:\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/icon-arrow-big-down.svg?v=1747231433\" alt=\"button down\"\u003e\u003c\/button\u003e\u003c\/span\u003e\n          \u003cdiv class=\"solid\" style=\"display: none;\"\u003e\u003c\/div\u003e\n          \u003cspan class=\"answer\" style=\"display: none;\"\u003eAbsolutely. Up to date NVIDIA drivers ensure optimal perofmance, compatibility, and reliability across professional applications.\u003c\/span\u003e\n        \u003c\/div\u003e\n    \u003c\/div\u003e\n  \u003c\/div\u003e\n\u003c\/div\u003e\n","products":[{"product_id":"nvidia-a800-pcie-gpu","title":"NVIDIA A800 40GB PCIe GPU","description":"\u003cdiv class=\"description\"\u003e\n\t\u003cdiv class=\"info\"\u003e\n\t\t\u003cp\u003eThe NVIDIA A800 is the China based market version of the NVIDIA A100 GPU. It was created to comply with U.S market and export. It uses Ampere architecture and HBM2 memory generation. It supports NVLink for multi GPU utilization, allowing a large memory pool by having a clsuter of multiple A800 GPUs. This GPU is best for AI \u0026amp; Machine Learning workloads, and High performance computing. It does not provide display port features, hence in order to display it needs a companion GPU such as the NVIDIA RTX400 Ada or other GPUs with disply ports. Compared to memory GDDR6\/GDDR7 architecture, HBM2 provides ultra-high bandwidth and wide buses, optimizing parallel throughput technology. \u003c\/p\u003e\n\t\u003c\/div\u003e\n\t\u003cdiv class=\"extra-info\"\u003e\n\t\t\u003ch3\u003e\u003cstrong\u003eKey Features:\u003c\/strong\u003e\u003c\/h3\u003e\n\t\t\u003ctable class=\"feature-table\"\u003e\n\t\t\t\u003ctbody\u003e\n\t\t\t    \u003ctr\u003e\n\t\t\t      \u003cth colspan=\"2\" style=\"background-color: #2ba22b; color:white;\"\u003eNVIDIA A800 40GB\u003c\/th\u003e\n\t\t\t  \u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eBrand\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eNVIDIA\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eModel #\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eA800\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eGPU Memory\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e40GB\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Generation\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eHBM2\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eCUDA Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e6,912\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Bandwidth\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e155.2GB\/s\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eInterface\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003ePCIe 4.0 x16\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eTensor Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e432\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eArchitecture\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eNVIDIA Ampere\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003ePower\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e240W Active\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDimensions\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eDual Slot FH \u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDisplay Capabilities\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eRequires companion GPU RTX 4000 ADA, RTX A4000\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n                \u003cth\u003eMPN\u003c\/th\u003e\n                \u003ctd\u003e900-51001-2200-000\u003c\/td\u003e\n              \u003c\/tr\u003e\n\t\t\t\u003c\/tbody\u003e\n\t\t\u003c\/table\u003e\n\t\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Default Title","offer_id":41631478251566,"sku":"NVIDIA-A800-40GB-PCIe","price":19226.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/nvidia-a800-front-left.png?v=1763496907"},{"product_id":"nvidia-h100-nvl-pcie-94gb-data-center-gpu","title":"NVIDIA H100 NVL PCIe 94GB Data Center GPU","description":"\u003cdiv class=\"description\"\u003e\n\t\u003cdiv class=\"info\"\u003e\n\t\t\u003cp\u003eThe NVIDIA H100 NVL PCIe is a high-end data center GPU, that supports the latest NVLink technology for GPU clustering. Engineered for AI professionals, engineers, and businesses dependent on AI \u0026amp; LLM training, this card has high compute power, efficiency, reliability and built on the latest HBM3 memory generation. This card is the entrance when it comes to enterprise data center AI workloads, for LLM training, AI Inference, Multi-model serving amongo other AI related..\u003c\/p\u003e\n\t\u003c\/div\u003e\n\t\u003cdiv class=\"extra-info\"\u003e\n\t\t\u003ch3\u003e\u003cstrong\u003eKey Features:\u003c\/strong\u003e\u003c\/h3\u003e\n\t\t\u003ctable class=\"feature-table\"\u003e\n\t\t\t\u003ctbody\u003e\n\t\t\t    \u003ctr\u003e\n\t\t\t      \u003cth colspan=\"2\" style=\"background-color: #2ba22b; color:white;\"\u003eNVIDIA H100 NVL PCIe 5.0 94GB\u003c\/th\u003e\n\t\t\t  \u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eBrand\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eNVIDIA\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eModel #\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eH100 NVL\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eGPU Memory\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e94GB\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Generation\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eHBM3\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eCUDA Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eN\/A \u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Bandwidth\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e3.9TB\/s\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eInterface\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003ePCIe 5.0 x16\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eTensor Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eN\/A\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eRay Tracing Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eN\/A\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003ePower\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e400W\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDimensions\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eDual Slot FH \u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDisplay Capabilities\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eN\/A\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n                \u003cth\u003eMPN\u003c\/th\u003e\n                \u003ctd\u003eN\/A\u003c\/td\u003e\n              \u003c\/tr\u003e\n\t\t\t\u003c\/tbody\u003e\n\t\t\u003c\/table\u003e\n\t\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Default Title","offer_id":41634875408430,"sku":"NVIDIA-H100-NVL-94GB-PCIe","price":39774.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/h100-nvl-right-reverse.png?v=1763570255"},{"product_id":"nvidia-l40s-48gb-data-center-gpu","title":"NVIDIA L40S 48GB Data Center GPU","description":"\u003cdiv class=\"description\"\u003e\n\t\u003cdiv class=\"info\"\u003e\n\t\t\u003cp\u003eThe NVIDIA L40S is a high-end data center GPU, running on GDDR6 memory and PCIe 4.0, meaning, systems on PCIe 4.0 Generations can run this GPU and get great performance for AI workloads. Engineered for AI professionals, engineers, businesses dependent on AI \u0026amp; LLM training, this card has high compute power, efficiency, reliability. This card is the entry level GPU when it comes to enterprise data center AI workloads, for LLM training, AI Inference, stable diffusion models, 3D rendering, real time ray-tracing, and AR\/VR Pipelines.\u003c\/p\u003e\n\t\u003c\/div\u003e\n\t\u003cdiv class=\"extra-info\"\u003e\n\t\t\u003ch3\u003e\u003cstrong\u003eKey Features:\u003c\/strong\u003e\u003c\/h3\u003e\n\t\t\u003ctable class=\"feature-table\"\u003e\n\t\t\t\u003ctbody\u003e\n\t\t\t    \u003ctr\u003e\n\t\t\t      \u003cth colspan=\"2\" style=\"background-color: #2ba22b; color:white;\"\u003eNVIDIA L40S 48GB\u003c\/th\u003e\n\t\t\t  \u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eBrand\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eNVIDIA\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eModel #\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eL40S\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eGPU Memory\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e48GB\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Generation\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eGDDR6\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eCUDA Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e18,176\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Bandwidth\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e864GB\/s\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eInterface\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003ePCIe 4.0 x16\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eTensor Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e568\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eRay Tracing Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e142\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003ePower\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e350W\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDimensions\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eDual Slot FH \u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDisplay Capabilities\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e4x DP(1.4) up to 8K 60Hz\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n                \u003cth\u003eMPN\u003c\/th\u003e\n                \u003ctd\u003eN\/A\u003c\/td\u003e\n              \u003c\/tr\u003e\n\t\t\t\u003c\/tbody\u003e\n\t\t\u003c\/table\u003e\n\t\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Default Title","offer_id":41635398844462,"sku":"NVIDIA-L40S-48GB-PCIe","price":10584.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/NVIDIA-L40S-Front-Left-Reverse-2.png?v=1763584460"},{"product_id":"nvidia-a16-64gb-data-center-gpu","title":"NVIDIA A16 64GB Data Center GPU","description":"\u003cdiv class=\"description\"\u003e\n\t\u003cdiv class=\"info\"\u003e\n\t\t\u003cp\u003eThe NVIDIA A16 is a high-end data center GPU, running on GDDR6 memory and PCIe 4.0, meaning, systems on PCIe 4.0 Generations can run this GPU and get great performance for AI model usage. Engineered for AI starters, graphical workloads, and businesses dependent on Virtual Desktop Infrastructure, this card has high compute power, efficiency, reliability. This card is the GPU when it comes to high density, graphics-rich virtual desktop infrastructure. Packed with 4 GPU chips within 1 PCIe card, it offers high concurrency ideal for virtualization purposes.\u003c\/p\u003e\n\t\u003c\/div\u003e\n\t\u003cdiv class=\"extra-info\"\u003e\n\t\t\u003ch3\u003e\u003cstrong\u003eKey Features:\u003c\/strong\u003e\u003c\/h3\u003e\n\t\t\u003ctable class=\"feature-table\"\u003e\n\t\t\t\u003ctbody\u003e\n\t\t\t    \u003ctr\u003e\n\t\t\t      \u003cth colspan=\"2\" style=\"background-color: #2ba22b; color:white;\"\u003eNVIDIA A16 64GB\u003c\/th\u003e\n\t\t\t  \u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eBrand\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eNVIDIA\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\u003cth\u003eModel #\u003c\/th\u003e\n\t\t\t\t\u003ctd\u003eA16\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eGPU Memory\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e64GB\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Generation\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eGDDR6\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eCUDA Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e5120\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eMemory Bandwidth\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e800GB\/s\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eInterface\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003ePCIe 4.0 x16\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eTensor Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e160\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eRay Tracing Cores\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e40\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003ePower\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003e250W\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDimensions\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eDual Slot FH \u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n\t\t\t\t\u003ctr\u003e\n\t\t\t\t\t\u003cth\u003eDisplay Capabilities\u003c\/th\u003e\n\t\t\t\t\t\u003ctd\u003eN\/A\u003c\/td\u003e\n\t\t\t\t\u003c\/tr\u003e\n              \u003ctr\u003e\n                \u003cth\u003eMPN\u003c\/th\u003e\n                \u003ctd\u003eN\/A\u003c\/td\u003e\n              \u003c\/tr\u003e\n\t\t\t\u003c\/tbody\u003e\n\t\t\u003c\/table\u003e\n\t\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Cloud Ninjas","offers":[{"title":"Default Title","offer_id":41636615192622,"sku":"NVIDIA-A16-64GB-PCIe","price":4224.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0248\/8539\/5502\/files\/nvidia-a16-top-right.png?v=1763653103"}],"url":"https:\/\/cloudninjas.com\/collections\/supermicro-sys-221h-tnr-server-gpu-upgrades.oembed","provider":"Cloud Ninjas","version":"1.0","type":"link"}