{"id":13227,"date":"2024-12-13T17:54:07","date_gmt":"2024-12-13T09:54:07","guid":{"rendered":"https:\/\/mvslinks.com\/?p=13227"},"modified":"2024-12-19T16:43:27","modified_gmt":"2024-12-19T08:43:27","slug":"simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx","status":"publish","type":"post","link":"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/","title":{"rendered":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX"},"content":{"rendered":"<p><span style=\"font-weight: 400;color: #000000\">NVIDIA&#8217;s H100\/H200, B100\/B200, B200\/GB200, and <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/hgx\/\" target=\"_blank\" rel=\"noopener\">HGX<\/a>\/DGX series are high-performance computing platforms designed for different computing needs and are widely used in artificial intelligence (AI), deep learning, big data analysis, scientific computing, and other fields. This article will focus on their differences and parameters.<\/span><\/p>\n<p>&nbsp;<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_74 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Changes_to_the_Nvidia_H200_and_H100\" >Changes to the Nvidia H200 and H100<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Difference_Between_Nvidia_B200_and_B100\" >Difference Between Nvidia B200 and B100<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Difference_Between_Nvidia_B200_and_GB200_HGX_and_DGX\" >Difference Between Nvidia B200 and GB200, HGX and DGX<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Learn_about_B200_and_GB200\" >Learn about B200 and GB200<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Learn_about_HGX_and_DGX\" >Learn about HGX and DGX<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Parameters_of_Nvidia_HGX_H100_and_H200\" >Parameters of Nvidia HGX H100 and H200<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Comparison_of_HGX_H200_and_HGX_H100\" >Comparison of HGX H200 and HGX H100<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Parameters_of_DGX_H100\" >Parameters of DGX H100<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Parameters_of_DGX_B200\" >Parameters of DGX B200<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Changes_to_the_Nvidia_H200_and_H100\"><\/span><span style=\"font-weight: 400;color: #000000\">Changes to the Nvidia H200 and H100<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;color: #000000\">The NVIDIA <a style=\"color: #000000\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/comparison-nvidia-a100-h100-l40s-h200-and-a6000\/\" target=\"_blank\" rel=\"noopener\">H100 and H200<\/a> series are primarily high-performance computing platforms based on the NVIDIA Hopper architecture. The <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/h100\/\" target=\"_blank\" rel=\"noopener\">H100<\/a> uses the latest Hopper architecture, which is deeply optimized for AI and HPC tasks.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">As an upgraded product of <a style=\"color: #000000\" href=\"https:\/\/www.naddod.com\/blog\/introduction-to-nvidia-dgx-h100-h200-system\" target=\"_blank\" rel=\"noopener\">H100<\/a>, <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/h200\/\" target=\"_blank\" rel=\"noopener\">H200<\/a> actually only upgrades the GPU memory related content in terms of overall parameters, and the GPU single card is upgraded from 80G HBM3 to 141G HBM3e (the memory capacity and type have changed), and the memory bandwidth has been increased from 3.35TB\/s to 4.8TB\/s, and the overall parameter comparison is as follows:<\/span><\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_13239\" aria-describedby=\"caption-attachment-13239\" style=\"width: 816px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-13239\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-1500x857.jpg\" alt=\"Parameters of NVIDIA H100 and H200\" width=\"816\" height=\"466\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-1500x857.jpg 1500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-500x286.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-768x439.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-1536x878.jpg 1536w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200-18x10.jpg 18w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Parameters-of-NVIDIA-H100-and-H200.jpg 1792w\" sizes=\"(max-width: 816px) 100vw, 816px\" \/><figcaption id=\"caption-attachment-13239\" class=\"wp-caption-text\"><span style=\"color: #000000\">Parameters of NVIDIA H100 and H200<\/span><\/figcaption><\/figure>\n<hr \/>\n<h2><\/h2>\n<h2><span class=\"ez-toc-section\" id=\"Difference_Between_Nvidia_B200_and_B100\"><\/span><span style=\"font-weight: 400;color: #000000\">Difference Between Nvidia B200 and B100<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Both the <a style=\"color: #000000\" href=\"https:\/\/www.anandtech.com\/show\/21310\/nvidia-blackwell-architecture-and-b200b100-accelerators-announced-going-bigger-with-smaller-data\" target=\"_blank\" rel=\"noopener\">B200 and B100<\/a> are data center GPUs based on NVIDIA&#8217;s latest generation Blackwell architecture. In terms of overall parameters, except for the specifications of the video memory, the computing power and power of other different precisions are different<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">As shown in the figure below, you can see that the TDP of <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/hgx\/\" target=\"_blank\" rel=\"noopener\">B100<\/a> is 700W. Some say it was designed to be compatible with the existing H100 server platform (head). However, in terms of comprehensive performance, B200 is better, for example, FP16 computing power is more than twice that of H100. At the same time, the TDP has also been increased to 1000W per card. Therefore, the server platform of the <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-b200\/\" target=\"_blank\" rel=\"noopener\">B200<\/a> needs to be redesigned, which is not compatible with the H100.<\/span><\/p>\n<p>&nbsp;<\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">Platform<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">GB200<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">B200<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">B100<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">HGX B200<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">HGX B100<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">Configuration<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">2x B200 GPU,<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">1x Grace CPU<\/span><\/td>\n<td><span style=\"color: #000000\"><a style=\"color: #000000\" href=\"https:\/\/datacrunch.io\/blog\/nvidia-blackwell-b100-b200-gpu\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400\">Blackwell<\/span><\/a><\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">GPU<\/span><\/td>\n<td><span style=\"color: #000000\"><a style=\"color: #000000\" href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-blackwell-platform-arrives-to-power-a-new-era-of-computing\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400\">Blackwell<\/span><\/a><\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">GPU<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">8x B200<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">GPU<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">8x B100<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">GPU<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">FP4 Tensor<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Dense\/Sparse<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">20\/40 petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">9\/18<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">7\/14<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">72\/144<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">56\/112<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">FP6\/FP8 Tensor<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Dense\/Sparse<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">10\/20 petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">4.5\/9<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">3.5\/7<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">36\/72<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">28\/56<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">INT8 Tensor<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Dense\/Sparse<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">10\/20 petaops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">4.5\/9<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">3.5\/7<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">36\/72<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">28\/56<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">FP16\/BF16 Tensor<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Dense\/Sparse<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">5\/10 petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">2.25\/4.5<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1.8\/3.5<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">18\/36<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">14\/28<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">TF32 Tensor<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Dense\/Sparse<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">2.5\/5 petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1.12\/2.25<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">0.9\/1.8<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">9\/18<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">7\/14<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">petaflops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">FP64 Tensor Dense<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">90 teraflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">40 teraflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">30 teraflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">320 teraflops<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">240 teraflops<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">Memory<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">384GB<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">(2x8x24GB)<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">192GB<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">(8x24GB)<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">192GB<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">(8x24GB)<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1536GB<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">(8x8x24GB)<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1536GB<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">(8x8x24GB)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">Bandwidth<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">16 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">8 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">8 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">64 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">64 TB\/s<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">NVLink Bandwidth<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">2x 1.8TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1.8 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1.8 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">14.4 TB\/s<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">14.4 TB\/s<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;color: #000000\">Power<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">Up to 2700W<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">1000W<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">700W<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">8000W<\/span><\/td>\n<td><span style=\"font-weight: 400;color: #000000\">5600W<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<hr \/>\n<h2><\/h2>\n<h2><span class=\"ez-toc-section\" id=\"Difference_Between_Nvidia_B200_and_GB200_HGX_and_DGX\"><\/span><span style=\"font-weight: 400;color: #000000\">Difference Between Nvidia B200 and GB200, HGX and DGX<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Learn_about_B200_and_GB200\"><\/span><strong><span style=\"color: #000000\">Learn about B200 and GB200<\/span><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">The B200 and GB200 series are NVIDIA&#8217;s GPU computing platforms that support GPU scaling and interconnection for tasks that require ultra-high throughput and low-latency computing.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">From the name, GB200 and B200 are easy to confuse, you can refer to the picture below.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">Jensen Huang on the far left is holding the <a style=\"color: #000000\" href=\"https:\/\/www.exxactcorp.com\/blog\/hpc\/comparing-nvidia-tensor-core-gpus\" target=\"_blank\" rel=\"noopener\">B200<\/a>, which is a standard NVIDIA GPU chip based on the Blackwell architecture. The <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/gb200-nvl72\/\" target=\"_blank\" rel=\"noopener\">GB200<\/a> is a &#8220;combination&#8221; of chips, as shown in the middle figure, which is a combination of 2 B200 and a Grace CPU (72-core ARM architecture processor) through a board. It is positioned as a dedicated &#8220;product&#8221;, which is designed by NVIDIA to build GPU &#8220;solution-level products&#8221; such as NVL72. As shown in the picture on the far right, it is the computing power node of NVL72, including 2 <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/gb200-nvl2\/\" target=\"_blank\" rel=\"noopener\">GB200<\/a>.<\/span><\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_13242\" aria-describedby=\"caption-attachment-13242\" style=\"width: 1349px\" class=\"wp-caption alignnone\"><img decoding=\"async\" class=\"wp-image-13242\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-2000x577.jpg\" alt=\"B200 and GB200\" width=\"1349\" height=\"390\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-2000x577.jpg 2000w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-1500x433.jpg 1500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-500x144.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-768x221.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-1536x443.jpg 1536w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-2048x591.jpg 2048w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/B200-and-GB200-18x5.jpg 18w\" sizes=\"(max-width: 1349px) 100vw, 1349px\" \/><figcaption id=\"caption-attachment-13242\" class=\"wp-caption-text\"><span style=\"color: #000000\">B200 and GB200<\/span><\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Learn_about_HGX_and_DGX\"><\/span><strong><span style=\"color: #000000\">Learn about HGX and DGX<\/span><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">The <a style=\"color: #000000\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/how-to-choose-nvidia-hgx-and-dgx\/\" target=\"_blank\" rel=\"noopener\">HGX and DGX<\/a> series are NVIDIA&#8217;s large-scale AI and high-performance computing platforms for enterprises and research institutions, often with multiple GPUs to support large-scale training and inference.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">As shown in the figure below, the core of the <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/hgx\/\" target=\"_blank\" rel=\"noopener\">HGX<\/a> product is 8 GPUs, which are integrated through the backplane, and also integrate <a style=\"color: #000000\" href=\"https:\/\/www.nvidia.com\/en-us\/design-visualization\/nvlink-bridges\/\" target=\"_blank\" rel=\"noopener\">NVLink<\/a> technology and <a style=\"color: #000000\" href=\"https:\/\/blogs.nvidia.com\/blog\/what-is-nvidia-nvlink\/\" target=\"_blank\" rel=\"noopener\">NVLink<\/a> SW chips. This &#8220;big guy&#8221; is designed by NVIDIA, and it is the &#8220;smallest form&#8221; of the H100 SXM GPU directly provided to the server manufacturer, of course, it cannot work independently, because it is a &#8220;logical big GPU&#8221;, which must be combined with the server platform (head) to form a complete GPU server.<\/span><\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_13238\" aria-describedby=\"caption-attachment-13238\" style=\"width: 818px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-13238\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247HGX.jpg\" alt=\"Picture of NVIDIA HGX\" width=\"818\" height=\"460\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247HGX.jpg 960w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247HGX-500x281.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247HGX-768x432.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247HGX-18x10.jpg 18w\" sizes=\"(max-width: 818px) 100vw, 818px\" \/><figcaption id=\"caption-attachment-13238\" class=\"wp-caption-text\"><span style=\"color: #000000\">Picture of NVIDIA HGX<\/span><\/figcaption><\/figure>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\"><a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-platform\/\" target=\"_blank\" rel=\"noopener\">DGX<\/a> is an NVIDIA-branded GPU server. As shown in the figure below, in addition to the core HGX module, it is equipped with the chassis, motherboard, power supply, CPU, memory, hard disk, network card and other components that the server should have.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;color: #000000\">It is not fundamentally different from the GPU servers based on HGX modules that we usually see from major server manufacturers. NVIDIA&#8217;s DGX machine is in competition with other server vendors. The first is that the price of DGX is high, and the second is to avoid market conflicts with server manufacturers.<\/span><\/p>\n<figure id=\"attachment_13237\" aria-describedby=\"caption-attachment-13237\" style=\"width: 814px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-13237\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247DGX.png\" alt=\"Picture of NVIDIA DGX\" width=\"814\" height=\"457\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247DGX.png 1070w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247DGX-500x281.png 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247DGX-768x431.png 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u56fe\u7247DGX-18x10.png 18w\" sizes=\"(max-width: 814px) 100vw, 814px\" \/><figcaption id=\"caption-attachment-13237\" class=\"wp-caption-text\"><span style=\"color: #000000\">Picture of NVIDIA DGX<\/span><\/figcaption><\/figure>\n<hr \/>\n<h2><\/h2>\n<h2><span class=\"ez-toc-section\" id=\"Parameters_of_Nvidia_HGX_H100_and_H200\"><\/span><span style=\"font-weight: 400;color: #000000\">Parameters of Nvidia HGX H100 and H200<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Comparison_of_HGX_H200_and_HGX_H100\"><\/span><span style=\"font-weight: 400;color: #000000\">Comparison of HGX H200 and HGX H100<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"color: #000000\"><a href=\"https:\/\/nvdam.widen.net\/s\/5kgbjq2v2t\/hpc-hgx-h100-datasheet-nvidia-web\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-13231\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/H100\u3001H200\u53c2\u6570\u5bf9\u6bd4\u8868.jpg\" alt=\"&quot;&lt;\/p\" width=\"807\" height=\"482\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/H100\u3001H200\u53c2\u6570\u5bf9\u6bd4\u8868.jpg 902w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/H100\u3001H200\u53c2\u6570\u5bf9\u6bd4\u8868-500x299.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/H100\u3001H200\u53c2\u6570\u5bf9\u6bd4\u8868-768x459.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/H100\u3001H200\u53c2\u6570\u5bf9\u6bd4\u8868-18x12.jpg 18w\" sizes=\"(max-width: 807px) 100vw, 807px\" \/><\/a><\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Parameters_of_DGX_H100\"><\/span><span style=\"font-weight: 400;color: #000000\">Parameters of DGX H100<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"color: #000000\"><a href=\"https:\/\/www.nvidia.com\/en-gb\/data-center\/dgx-h100\/\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-13236\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-H100.jpg\" alt=\"DGX H100\" width=\"824\" height=\"463\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-H100.jpg 1000w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-H100-500x281.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-H100-768x432.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-H100-18x10.jpg 18w\" sizes=\"(max-width: 824px) 100vw, 824px\" \/><\/a><\/span><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Parameters_of_DGX_B200\"><\/span><span style=\"font-weight: 400;color: #000000\">Parameters of DGX B200<\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"color: #000000\"><a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-b200\/\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-13235\" src=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-B200.jpg\" alt=\"DGX B200\" width=\"814\" height=\"375\" srcset=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-B200.jpg 788w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-B200-500x230.jpg 500w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-B200-768x354.jpg 768w, https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/\u63a2\u7d22DGX-B200-18x8.jpg 18w\" sizes=\"(max-width: 814px) 100vw, 814px\" \/><\/a><\/span><\/p>\n<hr \/>\n<h2><\/h2>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><span style=\"font-weight: 400;color: #000000\">Conclusion<\/span><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;color: #000000\">NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand, from efficient inference on a single GPU to training and inference acceleration at hyperscale data center level.<\/span><\/p>\n<p><span style=\"font-weight: 400;color: #000000\">When purchasing high-speed cable products, it is also crucial to choose a reliable supplier. <a style=\"color: #000000\" href=\"https:\/\/mvslinks.com\/th\/\" target=\"_blank\" rel=\"noopener\">MVSLINK<\/a> is a reliable provider of optical network solutions to build a fully connected, intelligent world through innovative computing and networking solutions.<\/span><\/p>","protected":false},"excerpt":{"rendered":"<p>NVIDIA&#8217;s H100\/H200, B100\/B200, B200\/GB200, and HGX\/DGX series are high-performance computing platforms designed for different computing needs and are widely used in artificial intelligence (AI), deep learning, big data analysis, scientific computing, and other fields. This article will focus on their differences and parameters. &nbsp; Changes to the Nvidia H200 and H100 The NVIDIA H100 and [&hellip;]<\/p>","protected":false},"author":2,"featured_media":13249,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"postBodyCss":"","postBodyMargin":[],"postBodyPadding":[],"postBodyBackground":{"backgroundType":"classic","gradient":""},"footnotes":""},"categories":[1],"tags":[],"post_folder":[],"class_list":["post-13227","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v23.0 (Yoast SEO v24.8.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX - mvslinks.com<\/title>\n<meta name=\"description\" content=\"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\" \/>\n<meta property=\"og:locale\" content=\"th_TH\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX\" \/>\n<meta property=\"og:description\" content=\"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\" \/>\n<meta property=\"og:site_name\" content=\"mvslinks.com\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/mvslink\/\" \/>\n<meta property=\"article:published_time\" content=\"2024-12-13T09:54:07+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-12-19T08:43:27+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"562\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Ella\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@mvslink\" \/>\n<meta name=\"twitter:site\" content=\"@mvslink\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ella\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 \u0e19\u0e32\u0e17\u0e35\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\"},\"author\":{\"name\":\"Ella\",\"@id\":\"https:\/\/mvslinks.com\/#\/schema\/person\/4f086077ef2e7af17e2d51143abffe7a\"},\"headline\":\"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX\",\"datePublished\":\"2024-12-13T09:54:07+00:00\",\"dateModified\":\"2024-12-19T08:43:27+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\"},\"wordCount\":936,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/mvslinks.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg\",\"articleSection\":[\"Blog\"],\"inLanguage\":\"th\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\",\"url\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\",\"name\":\"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX - mvslinks.com\",\"isPartOf\":{\"@id\":\"https:\/\/mvslinks.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg\",\"datePublished\":\"2024-12-13T09:54:07+00:00\",\"dateModified\":\"2024-12-19T08:43:27+00:00\",\"description\":\"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.\",\"breadcrumb\":{\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#breadcrumb\"},\"inLanguage\":\"th\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"th\",\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage\",\"url\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg\",\"contentUrl\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg\",\"width\":1000,\"height\":562,\"caption\":\"Simple Guide-NVIDIA H100-H200-B100-B200-B200-GB200-HGX-DGX\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/mvslinks.com\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/mvslinks.com\/#website\",\"url\":\"https:\/\/mvslinks.com\/\",\"name\":\"mvslinks.com\",\"description\":\"Factory Direct Supply Full Customized Optical Module for Data Center, Enterprise, HPC, Telecom\",\"publisher\":{\"@id\":\"https:\/\/mvslinks.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/mvslinks.com\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"th\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/mvslinks.com\/#organization\",\"name\":\"mvslinks.com\",\"url\":\"https:\/\/mvslinks.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"th\",\"@id\":\"https:\/\/mvslinks.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/04\/cropped-\u516c\u53f8logo-\u84dd-\u900f\u660e\u5e95-\u957f.png\",\"contentUrl\":\"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/04\/cropped-\u516c\u53f8logo-\u84dd-\u900f\u660e\u5e95-\u957f.png\",\"width\":1224,\"height\":411,\"caption\":\"mvslinks.com\"},\"image\":{\"@id\":\"https:\/\/mvslinks.com\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/mvslink\/\",\"https:\/\/x.com\/mvslink\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/mvslinks.com\/#\/schema\/person\/4f086077ef2e7af17e2d51143abffe7a\",\"name\":\"Ella\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"th\",\"@id\":\"https:\/\/mvslinks.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/mvslinks.com\/wp-content\/litespeed\/avatar\/c4942904fe1e967ee6c68b4735cfe8f3.jpg?ver=1775532272\",\"contentUrl\":\"https:\/\/mvslinks.com\/wp-content\/litespeed\/avatar\/c4942904fe1e967ee6c68b4735cfe8f3.jpg?ver=1775532272\",\"caption\":\"Ella\"},\"sameAs\":[\"https:\/\/mvslinks.com\/\"],\"url\":\"https:\/\/mvslinks.com\/th\/news\/blog\/author\/ella\/\"}]}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX - mvslinks.com","description":"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/","og_locale":"th_TH","og_type":"article","og_title":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX","og_description":"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.","og_url":"https:\/\/mvslinks.com\/th\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/","og_site_name":"mvslinks.com","article_publisher":"https:\/\/www.facebook.com\/mvslink\/","article_published_time":"2024-12-13T09:54:07+00:00","article_modified_time":"2024-12-19T08:43:27+00:00","og_image":[{"width":1000,"height":562,"url":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg","type":"image\/jpeg"}],"author":"Ella","twitter_card":"summary_large_image","twitter_creator":"@mvslink","twitter_site":"@mvslink","twitter_misc":{"Written by":"Ella","Est. reading time":"6 \u0e19\u0e32\u0e17\u0e35"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#article","isPartOf":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/"},"author":{"name":"Ella","@id":"https:\/\/mvslinks.com\/#\/schema\/person\/4f086077ef2e7af17e2d51143abffe7a"},"headline":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX","datePublished":"2024-12-13T09:54:07+00:00","dateModified":"2024-12-19T08:43:27+00:00","mainEntityOfPage":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/"},"wordCount":936,"commentCount":0,"publisher":{"@id":"https:\/\/mvslinks.com\/#organization"},"image":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage"},"thumbnailUrl":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg","articleSection":["Blog"],"inLanguage":"th","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/","url":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/","name":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX - mvslinks.com","isPartOf":{"@id":"https:\/\/mvslinks.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage"},"image":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage"},"thumbnailUrl":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg","datePublished":"2024-12-13T09:54:07+00:00","dateModified":"2024-12-19T08:43:27+00:00","description":"NVIDIA HGX and DGX platforms provide flexible solutions for AI and compute tasks of varying scale and demand.","breadcrumb":{"@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#breadcrumb"},"inLanguage":"th","potentialAction":[{"@type":"ReadAction","target":["https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/"]}]},{"@type":"ImageObject","inLanguage":"th","@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#primaryimage","url":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg","contentUrl":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/12\/Simple-Guide-NVIDIA-H100-H200-B100-B200-B200-GB200-HGX-DGX.jpg","width":1000,"height":562,"caption":"Simple Guide-NVIDIA H100-H200-B100-B200-B200-GB200-HGX-DGX"},{"@type":"BreadcrumbList","@id":"https:\/\/mvslinks.com\/news\/blog\/simple-guide-nvidia-h100-h200-b100-b200-b200-gb200-hgx-dgx\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/mvslinks.com\/"},{"@type":"ListItem","position":2,"name":"NVIDIA H100\/200\uff0cB100\/200\uff0cB200\/GB200\uff0cHGX\/DGX"}]},{"@type":"WebSite","@id":"https:\/\/mvslinks.com\/#website","url":"https:\/\/mvslinks.com\/","name":"mvslinks.com","description":"Factory Direct Supply Full Customized Optical Module for Data Center, Enterprise, HPC, Telecom","publisher":{"@id":"https:\/\/mvslinks.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/mvslinks.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"th"},{"@type":"Organization","@id":"https:\/\/mvslinks.com\/#organization","name":"mvslinks.com","url":"https:\/\/mvslinks.com\/","logo":{"@type":"ImageObject","inLanguage":"th","@id":"https:\/\/mvslinks.com\/#\/schema\/logo\/image\/","url":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/04\/cropped-\u516c\u53f8logo-\u84dd-\u900f\u660e\u5e95-\u957f.png","contentUrl":"https:\/\/mvslinks.com\/wp-content\/uploads\/2024\/04\/cropped-\u516c\u53f8logo-\u84dd-\u900f\u660e\u5e95-\u957f.png","width":1224,"height":411,"caption":"mvslinks.com"},"image":{"@id":"https:\/\/mvslinks.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/mvslink\/","https:\/\/x.com\/mvslink"]},{"@type":"Person","@id":"https:\/\/mvslinks.com\/#\/schema\/person\/4f086077ef2e7af17e2d51143abffe7a","name":"Ella","image":{"@type":"ImageObject","inLanguage":"th","@id":"https:\/\/mvslinks.com\/#\/schema\/person\/image\/","url":"https:\/\/mvslinks.com\/wp-content\/litespeed\/avatar\/c4942904fe1e967ee6c68b4735cfe8f3.jpg?ver=1775532272","contentUrl":"https:\/\/mvslinks.com\/wp-content\/litespeed\/avatar\/c4942904fe1e967ee6c68b4735cfe8f3.jpg?ver=1775532272","caption":"Ella"},"sameAs":["https:\/\/mvslinks.com\/"],"url":"https:\/\/mvslinks.com\/th\/news\/blog\/author\/ella\/"}]}},"_links":{"self":[{"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/posts\/13227"}],"collection":[{"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/comments?post=13227"}],"version-history":[{"count":12,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/posts\/13227\/revisions"}],"predecessor-version":[{"id":13700,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/posts\/13227\/revisions\/13700"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/media\/13249"}],"wp:attachment":[{"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/media?parent=13227"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/categories?post=13227"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/tags?post=13227"},{"taxonomy":"post_folder","embeddable":true,"href":"https:\/\/mvslinks.com\/th\/wp-json\/wp\/v2\/post_folder?post=13227"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}