{"id":5705,"date":"2025-02-07T12:51:21","date_gmt":"2025-02-07T12:51:21","guid":{"rendered":"https:\/\/directmacro.com\/blog\/?p=5705"},"modified":"2025-12-19T15:57:40","modified_gmt":"2025-12-19T15:57:40","slug":"gpu-hierarchy-benchmarks","status":"publish","type":"post","link":"https:\/\/directmacro.com\/blog\/post\/gpu-hierarchy-benchmarks","title":{"rendered":"GPU Hierarchy Benchmarks | Graphic Card Comparison"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1228.5px;margin-left: calc(-5% \/ 2 );margin-right: calc(-5% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:2.375%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:2.375%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:2.375%;--awb-spacing-left-medium:2.375%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:2.375%;--awb-spacing-left-small:2.375%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"Which GPU is best for deep learning?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Nvidia Data center GPUs such as Tesla A100 with ampere architecture and H100 with hopper architecture are the two best GPUs for deep learning.  NVIDIA RTX A6000 Tensor Core GPU is known for its performance as well as cost-effectiveness.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What determines GPU performance?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"A GPU\u2019s performance can be determined by its specification features, such as the number of core counts, clock speed, memory size, memory technology, and overall GPU tech architecture. Considering these elements, we draw a GPU benchmark comparison and their respective GPU Rankings in performance.\"\n    }\n  },{\n    \"@type\": \"Question\",\n    \"name\": \"What is the best GPU for streaming?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"The best budget GPUs with amazing streaming performance are RTX 4060 and RTX 3070 from Nvidia and Radeon RX 7800 XT and Radeon RX 7600 XT from AMD.\"\n    }\n  }]\n}\n<\/script><div class=\"fusion-content-boxes content-boxes columns row fusion-columns-1 fusion-columns-total-1 fusion-content-boxes-1 content-boxes-icon-with-title content-left\" style=\"--awb-item-margin-top:1px;--awb-item-margin-bottom:1px;--awb-margin-top:1px;--awb-margin-bottom:1px;--awb-hover-accent-color:var(--awb-color4);--awb-circle-hover-accent-color:var(--awb-color4);\" data-animationOffset=\"top-into-view\"><div style=\"--awb-backgroundcolor:rgba(255,255,255,0);\" class=\"fusion-column content-box-column content-box-column content-box-column-1 col-lg-12 col-md-12 col-sm-12 fusion-content-box-hover content-box-column-last content-box-column-last-in-row\"><div class=\"col content-box-wrapper content-wrapper link-area-box content-icon-wrapper-yes icon-hover-animation-none\" data-animationOffset=\"top-into-view\"><div class=\"heading heading-with-icon icon-left\"><div class=\"icon\"><span style=\"height:42px;width:42px;line-height:22px;border-color:rgba(255,255,255,0);border-width:1px;border-style:solid;background-color:var(--awb-color8);box-sizing:content-box;border-radius:50%;\"><i style=\"border-color:var(--awb-color8);border-width:1px;background-color:var(--awb-color7);box-sizing:content-box;height:40px;width:40px;line-height:40px;border-radius:50%;position:relative;top:auto;left:auto;margin:0;border-radius:50%;font-size:20px;\" aria-hidden=\"true\" class=\"fontawesome-icon fa-list-ul fas circle-yes\"><\/i><\/span><\/div><p class=\"content-box-heading\" style=\"--body_typography-font-size:24px;line-height:29px;\">Table of Contents<\/p><\/div><div class=\"fusion-clearfix\"><\/div><div class=\"content-container\">\n<hr \/>\n<\/div><\/div><\/div><div class=\"fusion-clearfix\"><\/div><\/div><div class=\"awb-toc-el awb-toc-el--1\" data-awb-toc-id=\"1\" data-awb-toc-options=\"{&quot;allowed_heading_tags&quot;:{&quot;h2&quot;:0},&quot;ignore_headings&quot;:&quot;&quot;,&quot;ignore_headings_words&quot;:&quot;&quot;,&quot;enable_cache&quot;:&quot;yes&quot;,&quot;highlight_current_heading&quot;:&quot;no&quot;,&quot;hide_hidden_titles&quot;:&quot;yes&quot;,&quot;limit_container&quot;:&quot;post_content&quot;,&quot;select_custom_headings&quot;:&quot;&quot;,&quot;icon&quot;:&quot;fa-angle-double-right fas&quot;,&quot;counter_type&quot;:&quot;custom_icon&quot;}\" style=\"--awb-margin-bottom:1px;--awb-item-font-family:&#039;Bookman Old Style&#039;, serif;--awb-item-font-style:italic;--awb-item-font-weight:700;--awb-item-overflow:hidden;--awb-item-white-space:nowrap;--awb-item-text-overflow:ellipsis;\"><div class=\"awb-toc-el__content\"><\/div><\/div><div class=\"fusion-text fusion-text-1\"><hr \/>\n<\/div><div class=\"fusion-text fusion-text-2\"><p><span style=\"font-weight: 400;\">The performance of a graphic processing unit is evaluated based on its specification. The Benchmarks tell what level of good performance it can offer. Therefore, it is important to understand the GPU hierarchy to analyze its expected performance. <a href=\"https:\/\/directmacro.com\/blog\/post\/what-is-optimal-cpu-and-gpu-temp\">GPUs<\/a> at different levels of the hierarchy may differ according to their price, features, and capabilities for different purposes. Some GPUs are best built for gaming, while they can still handle another graphic-intensive tasks. On the other hand, some top-tier GPUs are dedicated to producing high-end content, advanced rendering graphics, and data engineering. In This blog, we will explore the GPU hierarchy and its\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Begin by explaining the concept of GPU hierarchy and its significance in evaluating <a href=\"https:\/\/directmacro.com\/audio-video\/videos-graphics\/graphics-cards.html\">graphics card<\/a> performance.<\/span><\/p>\n<h2><strong>Graphics Card Hierarchy Top GPU Making Brands\u00a0<\/strong><\/h2>\n<p><span style=\"font-weight: 400;\">When it comes to GPU hierarchy, Nvidia and AMD are two major brands that are competing in the market. Although AMD is not a direct competition, for the last couple of years, it has been advancing towards better GPU designs at affordable prices. Therefore, AMD is emerging as a second choice for people who want to get access to advanced graphics within their budget.\u00a0<\/span><\/p>\n<h3><b>Nvidia<\/b><\/h3>\n<p><a href=\"https:\/\/directmacro.com\/audio-video\/videos-graphics\/graphics-cards\/nvidia.html\"><span style=\"font-weight: 400;\">Nvidia<\/span><\/a><span style=\"font-weight: 400;\"> has been pioneering innovation in GPUs since the launch of its first GPU in 1999. No doubt Nvidia has no comparison when it comes to GPU technology and the advanced science behind it. Nvidia\u2019s market share in the GPU market in the last quarter of 2023 was noticed at around 88%, while the other hand, <\/span><span style=\"font-weight: 400;\">AMD<\/span><span style=\"font-weight: 400;\"> stands at somewhere at 12%. Intel and other IT hardware manufacturers were trying to jump into the race; however, they were not able to give a solid setback to any of the two major GPU makers. \u00a0By the second quarter of 2024, AMD\u2019s Market share decreased by 0.2%, and by the last quarter of 2024, Nvidia hit the all-time high 90% of global GPU market share. According to different statistics, such as Yahoo Finance and Investing.com, it is 88%. However, despite the minimal variation, all agree with Nvidia\u2019s dominance as the GPU market leader.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Its data center GPUs are a key component in all AI advanced application-based large language models.\u00a0It collaborates with more than 20,000 companies through its GPU technology and AI solutions.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Nvidia\u2019s Blackwell Technology is a breakthrough in the GPU industry, and currently, its flagship GPU <a href=\"https:\/\/directmacro.com\/blog\/post\/rtx-5090-release-date\">RTX 5090<\/a> from Rtx 50 Series is the most powerful graphic card in the world right now.<\/span><\/p>\n<h3><b>Graphics Card Hierarchy from Nvidia<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Nvidia began its RTX 10 series back in 2016, and now, almost after a decade, it has evolved to <a href=\"https:\/\/directmacro.com\/blog\/post\/nvidia-rtx-50-series-gpus\">RTX 50 Series<\/a>. Nvidia just recently uncovered its RTX 50 series at <\/span><a href=\"https:\/\/www.ces.tech\/\"><span style=\"font-weight: 400;\">CES 2025<\/span><\/a><span style=\"font-weight: 400;\">. Here is the list of GPU series and their Architecture.<\/span><\/p>\n<\/div>\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<table style=\"height: 1053px;\" width=\"956\">\n<tbody>\n<tr>\n<td><b>Series<\/b><\/td>\n<td><b>Architecture<\/b><\/td>\n<td><b>GPUs\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RTX 50 Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Blackwell Architecture<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 5090<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 5080<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 5070, RTX 5070 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 5060, RTX 5060 Ti<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RTX 40 Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Ada Lovelace Architecture\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4090<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4080 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4070 Ti Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4070 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4060 Ti (16GB \/ 8GB)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4060<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RTX 30 Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Ampere<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3090 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3090<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3080 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3080<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3060 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3060<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3050<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RTX 20 Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Turing<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 2080 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 2080 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 2070 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 2060 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 2060<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div class=\"fusion-text fusion-text-3\"><p><span style=\"font-weight: 400;\">Before its RTX series, Nvidia had a GPU series named GTX. The GPU card hierarchy from the Nvidia GTX series is as follows:<\/span><\/p>\n<\/div>\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<h3><b>Nvidia GTX Series<\/b><\/h3>\n<table style=\"height: 455px;\" width=\"956\">\n<tbody>\n<tr>\n<td><b>GTX series\u00a0<\/b><\/td>\n<td><b>Architecture<\/b><\/td>\n<td><b>GPUs\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">GTX 16 Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Turing<\/span><\/td>\n<td><span style=\"font-weight: 400;\">GTX 1660 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1660 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1660<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1650, GTX 1650 Super<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">GTX 10 Series<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Pascal<\/span><\/td>\n<td><span style=\"font-weight: 400;\">GTX 1080,\u00a0 GTX 1080 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1070, GTX 1070 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1060 (6GB \/ 3GB)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1050 Ti, GTX 1050<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<h3><b>Nvidia DATA Center GPU Hierarchy<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Nvidia offers some data center GPUs that are designed for high-performance computing, machine learning, and cloud computing.<\/span><\/p>\n<table style=\"height: 343px;\" width=\"955\">\n<tbody>\n<tr>\n<td><b>Data Center GPUs Series\u00a0<\/b><\/td>\n<td><b>Architecture\u00a0<\/b><\/td>\n<td><b>Top GPU Models\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">H- Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Hopper Architecture<\/span><\/td>\n<td><span style=\"font-weight: 400;\">H200, H100<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">A- Series<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Ampere Architecture<\/span><\/td>\n<td><span style=\"font-weight: 400;\">A100, A40<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">L-Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Ada Lovelace<\/span><\/td>\n<td><span style=\"font-weight: 400;\">L40S, L40<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">V-Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Volta Architecture\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">V100, V100S<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">P-Series\u00a0<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Pascal<\/span><\/td>\n<td><span style=\"font-weight: 400;\">P100, P40<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div class=\"fusion-text fusion-text-4\"><h3><b>Entry Level GPUs vs Mid-Level GPUs vs Top Tier GPUs<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Currently, Nvidia\u2019s RTX 5090 is considered the world\u2019s most powerful GPU. It has recently been released in the largest tech event of CES 2025. It became available in the market on 31st Jan 2025. Nvidia\u2019s top-tier GPUs contain around 12 GB GDDR6X, while the mid-range GPUS\u00a0has 8 GB GDDR6 GPUs IN RTX 40 and 30 series. \u00a0On the other hand, the entry-level GPUs in the GPU benchmark list have a minimum memory of 8 to 6 GB of either <a href=\"https:\/\/directmacro.com\/blog\/post\/gddr6-vs-gddr6x-graphics-memory\">GDDR6<\/a> or GDDR5 Technology.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is the chart showing GPU hierarchy according to GPU performance comparison:<\/span><\/p>\n<\/div>\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<table style=\"height: 358px;\" width=\"949\">\n<tbody>\n<tr>\n<td><b>Top Tier GPUs<\/b><\/td>\n<td><b>Mid-Level GPUs<\/b><\/td>\n<td><b>Entry Level GPUs<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RTX 5090\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 5080<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4080 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4080<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3090 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3090 Ti<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4070 Ti Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4070 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4070<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4060 Ti (16GB \/ 8GB)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 4060<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3070 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3070<\/span><\/p>\n<p><span style=\"font-weight: 400;\">RTX 3060 Ti<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3050 (8GB \/ 6GB)<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1660 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1660 Ti<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1650 Super<\/span><\/p>\n<p><span style=\"font-weight: 400;\">GTX 1650<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div class=\"fusion-text fusion-text-5\"><h3><b>AMD GPUs<\/b><\/h3>\n<p><a href=\"https:\/\/directmacro.com\/manufacturers\/amd.html\"><span style=\"font-weight: 400;\">AMD<\/span><\/a><span style=\"font-weight: 400;\"> Advanced Micro Device Manufacturer is an American hardware manufacturing company that creates microprocessors and related technologies. AMD&#8217;s core product lines are processors and accelerators for both individual uses as well as for servers. Currently, AMD holds around 12% of the global GPU industry market share.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Recently, AMD announced its integration into the new <\/span><span style=\"font-weight: 400;\">Deep seek V-3 model<\/span><span style=\"font-weight: 400;\">. Until now, Nvidia has been providing data center chips and advanced processors to AI giants that deal with large language models, cloud computing, and deep learning AI training. However, after the introduction of the Deep Seek V3 Model, which is open source and offers multimodal design to bring unparalleled efficiency. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Although it has a small market share in the GPU market, AMD still never stays behind the game when it comes to catching up with advanced technology. Even in center processing units, it is striving to compete with Intel, the biggest player in the CPU Market. AMD\u2019s two major brands are Ryzen for CPU and Radeon for GPUs. In addition, the AMD Instinct MI series offers AI and data center GPUs, such as Mi300X and M1250, which compete with <\/span><a href=\"https:\/\/directmacro.com\/blog\/post\/nvidia-h100-a-new-revolution-to-gpus-artificial-intelligence\"><span style=\"font-weight: 400;\">Nvidia\u2019s H100<\/span><\/a><span style=\"font-weight: 400;\"> and A100.<\/span><\/p>\n<h3><b>Graphics Card Hierarchy of AMD GPUs<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Considering GPU benchmark comparison, the most powerful GPU from AMD is going to be RX 9070, which is going to arrive in March 2025, as AMD officially disclosed in CES 2025. According to the AMD GPU benchmark list, the top-tier AMD GPUs have 20 GB to 24 GB <a href=\"https:\/\/directmacro.com\/blog\/post\/vram-explained-why-modern-games-demand-more-of-vram\">VRAM<\/a>.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is the list of GPU hierarchies according to the GPU benchmark specifications.<\/span><\/p>\n<\/div>\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<table style=\"height: 395px;\" width=\"955\">\n<tbody>\n<tr>\n<td><b>Top Tier GPUs of AMD\u00a0\u00a0<\/b><\/td>\n<td><b>Architecture\u00a0<\/b><\/td>\n<td><b>Vram\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 9000 Series (Upcoming)<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 4<\/span><\/td>\n<td><span style=\"font-weight: 400;\"> TBD\u00a0<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7900 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 3<\/span><\/td>\n<td><span style=\"font-weight: 400;\">20GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7900 XTX<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 3<\/span><\/td>\n<td><span style=\"font-weight: 400;\">24GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7900 GRE<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 3<\/span><\/td>\n<td><span style=\"font-weight: 400;\">16GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon PRO W7900<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 3<\/span><\/td>\n<td><span style=\"font-weight: 400;\">48GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 6950 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RDNA 2<\/span><\/td>\n<td><span style=\"font-weight: 400;\">16GB GDDR6<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<p><span style=\"font-weight: 400;\">The mid-level AMD GPUs come with 16 to 8 GB of VRAM. All of them support 1140p Ultra resolution and have a high frame per second. These are perfect for 1080 ultra gaming.\u00a0<\/span><\/p>\n<table style=\"height: 311px;\" width=\"958\">\n<tbody>\n<tr>\n<td><b>AMD\u2019s Mid-Level GPUs<\/b><\/td>\n<td><b>Nvidia Equivalent<\/b><\/td>\n<td><b>Vram\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7800 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4070 Super<\/span><\/td>\n<td><span style=\"font-weight: 400;\">16 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7700 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4060 Ti<\/span><\/td>\n<td><span style=\"font-weight: 400;\">12 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7600 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4060<\/span><\/td>\n<td><span style=\"font-weight: 400;\">16 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7600<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 4060 \/ RTX 3060<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB GDDR6<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n\n<div class=\"table-1\" style=\"--awb-margin-bottom:30px;\">\n<p><span style=\"font-weight: 400;\">In AMD\u2019s GPU hierarchy, the entry-level GPU has benchmarks that seamlessly support 1080p gaming, but they can\u2019t support high-end gaming due to limited ray tracing technology. They are manufactured with RDNA2 Architecture and support a Vram of 8GB to 6GB.<\/span><\/p>\n<table style=\"height: 336px;\" width=\"948\">\n<tbody>\n<tr>\n<td><b>AMD\u2019s Mid-Level GPUs<\/b><\/td>\n<td><b>Nvidia Equivalent<\/b><\/td>\n<td><b>Vram\u00a0<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 7600<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3060<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 6650 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3050\/ 3060<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 6600 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3050 Ti<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 6600<\/span><\/td>\n<td><span style=\"font-weight: 400;\">RTX 3050<\/span><\/td>\n<td><span style=\"font-weight: 400;\">8 GB GDDR6<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Radeon RX 6500 XT<\/span><\/td>\n<td><span style=\"font-weight: 400;\">GTX 1650 Super<\/span><\/td>\n<td><span style=\"font-weight: 400;\">4 GB GDDR6<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<div class=\"fusion-text fusion-text-6\"><h3><b>Intel Qualcomm, Tesla &amp; Google<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Besides AMD and Nvidia, Intel, Qualcomm, Tesla &amp; Google also make GPUs on a smaller scale. However, their GPUs are mostly used in entry-level graphics; they can\u2019t offer completion to advanced technology provided by Nvidia and AMD.<\/span><\/p>\n<h2><b>Third-Party Brands Offering Custom Variation of the GPUs\u00a0<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Nvidia and AMD are the two most popular Graphic processor manufacturers. However, there are many third-party brands that buy their GPUs, make value additions, and sell them on the market. These brand design their own PCBs, cooling solutions, and power supply and rebrand the GPU with their name. The most popular third-party GPU brands are as follows:<\/span><\/p>\n<ul>\n<li aria-level=\"1\"><b>ASUS,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>MSI,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>Gigabyte,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>EVGA,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>ZOTAC,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>Sapphire,\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>XFX<\/b><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">The value Additions these brand makes are:<\/span><\/p>\n<ul>\n<li aria-level=\"1\"><b>Custom Overclocking<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>RGB lighting\u00a0<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>Adding Vapor Chamber Cooling<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>Military-Grade Capacitors<\/b><\/li>\n<\/ul>\n<ul>\n<li aria-level=\"1\"><b>Better VRMs &amp; Power Delivery<\/b><\/li>\n<\/ul>\n<h2><b>Conclusion<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">In conclusion, when it comes to GPU ranking and performance, Nvidia and AMD are two major players in the market. When we do a GPU performance comparison, both manufacturers offer a variety of GPUs to cater to different workload requirements. However, AMD is considered a bit more reasonable than Nvidia.<\/span><\/p>\n<\/div><div class=\"fusion-text fusion-text-7\"><h2><b>FAQs<\/b><\/h2>\n<p><b>Which GPU is best for deep learning?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Nvidia Data center GPUs such as Tesla A100 with ampere architecture and H100 with hopper architecture are the two best GPUs for deep learning.\u00a0 NVIDIA RTX A6000 Tensor Core GPU is known for its performance as well as cost-effectiveness.<\/span><\/p>\n<p><b>What determines GPU performance?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">A GPU&#8217;s performance can be determined by its specification features, such as the number of core counts, clock speed, memory size, memory technology, and overall GPU tech architecture. Considering these elements, we draw a GPU benchmark comparison and their respective GPU Rankings in performance.<\/span><\/p>\n<p><b>What is the best GPU for streaming?<\/b><\/p>\n<p><span style=\"font-weight: 400;\">The best budget GPUs with amazing streaming performance are RTX 4060 and RTX 3070 from Nvidia and Radeon <a href=\"https:\/\/directmacro.com\/blog\/post\/amd-radeon-rx-7800-xt\">RX 7800 XT<\/a> and Radeon RX 7600 XT from AMD. <\/span><\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":18,"featured_media":5706,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[100,484],"tags":[521,520,389],"class_list":["post-5705","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-graphics-card","category-guides","tag-gpu-benchmarks-hierarchy","tag-gpu-hierarchy","tag-graphics-cards"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.8 (Yoast SEO v26.9) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>GPU Hierarchy Benchmarks | Graphic Card Comparison<\/title>\n<meta name=\"description\" content=\"Learn the in-depth GPU hierarchy with the best benchmarks. 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