{"id":115263,"date":"2026-08-10T09:47:50","date_gmt":"2026-08-10T08:47:50","guid":{"rendered":"https:\/\/mcomputers.cz\/?p=115263"},"modified":"2026-08-13T13:10:46","modified_gmt":"2026-08-13T12:10:46","slug":"comparison-of-hpc-accelerators-2026","status":"publish","type":"post","link":"https:\/\/mcomputers.cz\/en\/2026\/08\/10\/comparison-of-hpc-accelerators-2026\/","title":{"rendered":"Comparison of HPC Accelerators 2026"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-6oeo6ab-0e5c1210bf9f541e4fa62d4279baf11c main_color avia-section-default avia-no-border-styling  avia-builder-el-0  el_before_av_section  avia-builder-el-first  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><main  role=\"main\" itemprop=\"mainContentOfPage\"  class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n<div  class='flex_column av-632vkk3-431739796aaaebb5d2691474b74247ac av_one_half  avia-builder-el-1  el_before_av_one_half  avia-builder-el-first  first flex_column_div  '     ><section  class='av_textblock_section av-m5gtj1ub-400921b0063936e827a168052f491bc5 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Comparison of HPC Accelerators for 2026<\/h2>\n<p><strong>August 10, 2026<\/strong><\/p>\n<p>Every year, companies introduce new and unique accelerators and solutions for HPC that drive major advancements in the development, research, and production of LLMs, generative AI, and complex scientific computations. That\u2019s why we\u2019ve summarized the most significant ones for 2026, compared their individual specifications and performance, and outlined their key features.<\/p>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-5ty40b7-4530fbfedbbeea4cb30da17f9abd348a\">\n#top .hr.hr-invisible.av-5ty40b7-4530fbfedbbeea4cb30da17f9abd348a{\nheight:50px;\n}\n<\/style>\n<div  class='hr av-5ty40b7-4530fbfedbbeea4cb30da17f9abd348a hr-invisible  avia-builder-el-3  el_after_av_textblock  el_before_av_social_share '><span class='hr-inner '><span class=\"hr-inner-style\"><\/span><\/span><\/div><br \/>\n<div  class='av-social-sharing-box av-54472k3-e7390fa12778012da7410a4dd7109bd8 av-social-sharing-box-circle  avia-builder-el-4  el_after_av_hr  avia-builder-el-last  social-icons av-social-sharing-box-color-bg av-social-sharing-box-same-width'><div class=\"av-share-box\"><h5 class='av-share-link-description av-no-toc '>Share this post<\/h5><ul 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av-4vbtboz-daaec48c469f5584ba295a08755e7e7e av_one_half  avia-builder-el-5  el_after_av_one_half  el_before_av_hr  flex_column_div  '     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-m5gtld6c-e45f2ec50138b0536cc597c42fb6ef5d\">\n.avia-image-container.av-m5gtld6c-e45f2ec50138b0536cc597c42fb6ef5d img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-m5gtld6c-e45f2ec50138b0536cc597c42fb6ef5d .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-m5gtld6c-e45f2ec50138b0536cc597c42fb6ef5d av-styling- avia-align-center  avia-builder-el-6  avia-builder-el-no-sibling '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-115076 avia-img-lazy-loading-not-115076 avia_image ' src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail.avif\" alt='AMD Epyc CPU 5. gen.' title='PIA-epyc-9005-series-processors-hero-Thumbnail'  height=\"675\" width=\"1200\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail.avif 1200w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail-300x169.avif 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail-1030x579.avif 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail-768x432.avif 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/PIA-epyc-9005-series-processors-hero-Thumbnail-705x397.avif 705w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/div><\/div><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-4al7r3n-d6a87e4bfc5a9299ddc00245b0e009a5\">\n#top .hr.av-4al7r3n-d6a87e4bfc5a9299ddc00245b0e009a5{\nmargin-bottom:30px;\n}\n.hr.av-4al7r3n-d6a87e4bfc5a9299ddc00245b0e009a5 .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-4al7r3n-d6a87e4bfc5a9299ddc00245b0e009a5 hr-custom  avia-builder-el-7  el_after_av_one_half  avia-builder-el-last  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n\n<\/div><\/div><\/main><!-- close content main element --><\/div><\/div><div id='av_section_2'  class='avia-section av-dyziyb-4e31b68ce23df69e8b6c99f85254f3f3 main_color avia-section-default avia-no-border-styling  avia-builder-el-8  el_after_av_section  el_before_av_one_full  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n<div  class='flex_column av-3a0ymwj-f56e448e43d58a5f548cfc2193f42f53 av_one_half  avia-builder-el-9  el_before_av_one_half  avia-builder-el-first  first flex_column_div  '     ><section  class='av_textblock_section av-m5gtjs0y-2e823c06c80d74f25c4391176e2f16e7 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h3>Overview<\/h3>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-lbkrkld2-caba850676e52989ab0ed098b1c96c10 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p>Computational accelerators now play a completely dominant role in HPC and AI data centers. Instead of having all work processed by traditional processors, computations are distributed across specialized units with a tailored instruction set, tensor cores, or extremely fast HBM memory to process complex matrix operations many times faster.<\/p>\n<p>While modern server processors today reach up to 192 cores, computing accelerators contain thousands to hundreds of thousands of them. Furthermore, today\u2019s market is shifting from standalone PCIe cards to massive rack-based architectures, interconnected chiplets, and entire silicon wafers.<\/p>\n<p>Manufacturers are constantly pushing the boundaries of architecture, memory bandwidth, and interconnects. To help you better understand current trends and get a good overview of the available options, we\u2019ve put together this comparison of the latest products on the market.<\/p>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbkrjfry-46bb653f5c17e6b121ea96a73550609e\">\n.avia-image-container.av-lbkrjfry-46bb653f5c17e6b121ea96a73550609e img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-lbkrjfry-46bb653f5c17e6b121ea96a73550609e .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-lbkrjfry-46bb653f5c17e6b121ea96a73550609e av-styling- avia-align-center  avia-builder-el-12  el_after_av_textblock  avia-builder-el-last '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-114626 avia-img-lazy-loading-not-114626 avia_image ' src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/vera-rubin-cluster.png\" alt='Vera Rubin Cluster' title='Vera Rubin Cluster'  height=\"500\" width=\"999\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/vera-rubin-cluster.png 999w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/vera-rubin-cluster-300x150.png 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/vera-rubin-cluster-768x384.png 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/vera-rubin-cluster-705x353.png 705w\" sizes=\"(max-width: 999px) 100vw, 999px\" \/><\/div><\/div><\/div><\/p><\/div><div  class='flex_column av-2uvnpxv-d733aebb851a9f360d62048f42a996ef av_one_half  avia-builder-el-13  el_after_av_one_half  avia-builder-el-last  flex_column_div  '     ><section  class='av_textblock_section av-lbqfvluv-25bc3f43fdab513a0d2f2591c35852aa '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h3>Individual accelerators<\/h3>\n<\/div><\/section><br \/>\n<div  class='avia-buttonrow-wrap av-lbqfh6on-36989f87383559ce8a17e514bdce4e93 avia-buttonrow-left  avia-builder-el-15  el_after_av_textblock  avia-builder-el-last '>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-6-af129f0f89505fd384ec97643000953f\">\n#top #wrap_all .avia-button.av-lbqfdypc-6-af129f0f89505fd384ec97643000953f{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#nvidia'  class='avia-button av-lbqfdypc-6-af129f0f89505fd384ec97643000953f avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"NVIDIA B300 \/ Vera Rubin (R100)\"><span class='avia_iconbox_title' >NVIDIA B300 \/ Vera Rubin (R100)<\/span><\/a>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-7-cad9f5a2f21f85e62014477b2fbbd242\">\n#top #wrap_all .avia-button.av-lbqfdypc-7-cad9f5a2f21f85e62014477b2fbbd242{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#amd'  class='avia-button av-lbqfdypc-7-cad9f5a2f21f85e62014477b2fbbd242 avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"AMD MI455X \/ 430X\"><span class='avia_iconbox_title' >AMD MI455X \/ 430X<\/span><\/a>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-8-9a27c8e385c7d4513cbbb17b6adcfd13\">\n#top #wrap_all .avia-button.av-lbqfdypc-8-9a27c8e385c7d4513cbbb17b6adcfd13{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#intel'  class='avia-button av-lbqfdypc-8-9a27c8e385c7d4513cbbb17b6adcfd13 avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"Intel Gaudi 3\"><span class='avia_iconbox_title' >Intel Gaudi 3<\/span><\/a>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-4-76af493ef049c54ce05e76af648b44ee\">\n#top #wrap_all .avia-button.av-lbqfdypc-4-76af493ef049c54ce05e76af648b44ee{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#groq'  class='avia-button av-lbqfdypc-4-76af493ef049c54ce05e76af648b44ee avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"Groq LPU\"><span class='avia_iconbox_title' >Groq LPU<\/span><\/a>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-4-2-5ee796d630fcf6acc2088eaedbc0104c\">\n#top #wrap_all .avia-button.av-lbqfdypc-4-2-5ee796d630fcf6acc2088eaedbc0104c{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#cerebras'  class='avia-button av-lbqfdypc-4-2-5ee796d630fcf6acc2088eaedbc0104c avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"Cerebras WSE-3\"><span class='avia_iconbox_title' >Cerebras WSE-3<\/span><\/a>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbqfdypc-4-1-c99f4263577a1bc73c6bb0bb5d9fb2dc\">\n#top #wrap_all .avia-button.av-lbqfdypc-4-1-c99f4263577a1bc73c6bb0bb5d9fb2dc{\nmargin-bottom:5px;\nmargin-right:5px;\n}\n<\/style>\n<a href='#huawei'  class='avia-button av-lbqfdypc-4-1-c99f4263577a1bc73c6bb0bb5d9fb2dc avia-icon_select-no avia-size-small avia-color-theme-color'   aria-label=\"Huawei Ascend 950PR\"><span class='avia_iconbox_title' >Huawei Ascend 950PR<\/span><\/a>\n<\/div><\/p><\/div><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_2'  class='main_color av_default_container_wrap container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'><div  class='flex_column av-gi8gpar-d8fd612824715b520f1806d971279c0b av_one_full  avia-builder-el-16  el_after_av_section  el_before_av_one_full  avia-builder-el-first  first flex_column_div  '     ><section  class='av_textblock_section av-lbkrt1cy-0724f4844e589144dce0123f73b6dd4f '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Accelerator parameters<\/h2>\n<\/div><\/section><br \/>\n<div class='avia-data-table-wrap av-1ljk5bn-fa21ccd5a72f664d0650b9356208e8d2 avia_responsive_table avia-table-1'><table  class='avia-table avia-data-table avia_pricing_default  avia-builder-el-18  el_after_av_textblock  el_before_av_textblock '  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/Table\" ><tbody><tr class=''><td class=''>Company<\/td><td class='avia-center-col'>NVIDIA<\/td><td class='avia-center-col'>NVIDIA<\/td><td class='avia-center-col'>AMD<\/td><td class='avia-center-col'>AMD<\/td><td class='avia-center-col'>Intel<\/td><td class='avia-center-col'>Groq<\/td><td class='avia-center-col'>Cerebras<\/td><td class='avia-center-col'>Huawei<\/td><\/tr><tr class=''><td class=''>Accelerator<\/td><td class='avia-center-col'>B300<\/td><td class='avia-center-col'>Vera Rubin (R100)<\/td><td class='avia-center-col'>MI455X<\/td><td class='avia-center-col'>MI430X<\/td><td class='avia-center-col'>Gaudi 3<\/td><td class='avia-center-col'>Groq LPU<\/td><td class='avia-center-col'>WSE-3<\/td><td class='avia-center-col'>Ascend 950PR<\/td><\/tr><tr class=''><td class=''>Number of cores<\/td><td class='avia-center-col'>20,480<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>256 WGP<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>64 TPC<\/td><td class='avia-center-col'>1 TSP<\/td><td class='avia-center-col'>900,000<\/td><td class='avia-center-col'>TB\/A<\/td><\/tr><tr class=''><td class=''>Transistor count<\/td><td class='avia-center-col'>208 billion<\/td><td class='avia-center-col'>336 billion<br \/>\n<\/td><td class='avia-center-col'>320 billion<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>4,000 billion<\/td><td class='avia-center-col'>TB\/A<\/td><\/tr><tr class=''><td class=''>Manufacturing process<\/td><td class='avia-center-col'>5 nm<\/td><td class='avia-center-col'>3 nm<\/td><td class='avia-center-col'>2 nm<\/td><td class='avia-center-col'>2 nm<\/td><td class='avia-center-col'>5 nm<\/td><td class='avia-center-col'>4 nm<\/td><td class='avia-center-col'>5 nm<\/td><td class='avia-center-col'>5 nm<\/td><\/tr><tr class=''><td class=''>Capacity<\/td><td class='avia-center-col'>288 GB<\/td><td class='avia-center-col'>288 GB<\/td><td class='avia-center-col'>432 GB<\/td><td class='avia-center-col'>432 GB<\/td><td class='avia-center-col'>128 GB<\/td><td class='avia-center-col'>230 MB<\/td><td class='avia-center-col'>44 GB<\/td><td class='avia-center-col'>112 GB<\/td><\/tr><tr class=''><td class=''>Memory type<\/td><td class='avia-center-col'>HBM3e<\/td><td class='avia-center-col'>HBM4<\/td><td class='avia-center-col'>HBM4<\/td><td class='avia-center-col'>HBM4<\/td><td class='avia-center-col'>HBM2e<\/td><td class='avia-center-col'>on-chip SRAM<\/td><td class='avia-center-col'>on-chip SRAM<\/td><td class='avia-center-col'>HiBL (prop.)<\/td><\/tr><tr class=''><td class=''>Bus<br \/>\n<\/td><td class='avia-center-col'>NVLink 5<\/td><td class='avia-center-col'>NVLink 6<\/td><td class='avia-center-col'>UALink \/ PCIe Gen 6<\/td><td class='avia-center-col'>UALink \/ PCIe Gen 6<\/td><td class='avia-center-col'>RoCE \/ PCIe Gen 5<\/td><td class='avia-center-col'>PCIe\/prop.<\/td><td class='avia-center-col'>prop.<\/td><td class='avia-center-col'>LinQu\/HCCS<\/td><\/tr><tr class=''><td class=''>Consumption<\/td><td class='avia-center-col'>1,400 W<\/td><td class='avia-center-col'>2,300 W<\/td><td class='avia-center-col'>900 W<\/td><td class='avia-center-col'>900 W<\/td><td class='avia-center-col'>900 W<\/td><td class='avia-center-col'>70 W<\/td><td class='avia-center-col'>27 kW<\/td><td class='avia-center-col'>600 W<\/td><\/tr><tr class=''><td class=''>Price<\/td><td class='avia-center-col'>53,000 USD*<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>15,625 USD*<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>N\/A<br \/>\n<\/td><td class='avia-center-col'>9,600 USD*<\/td><\/tr><\/tbody><\/table><\/div><br \/>\n<section  class='av_textblock_section av-livrmiem-0cab25b5c27251eb133eb08234d4ef3a '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p style=\"font-size: 11;\">* These specifications are only estimates and have not been verified; they may change over time<\/p>\n<\/div><\/section><\/p><\/div><\/p>\n<div  class='flex_column av-10qp12c3-18c51841157f7c77d7ab778156667ef9 av_one_full  avia-builder-el-20  el_after_av_one_full  el_before_av_one_full  first flex_column_div  column-top-margin'     ><section  class='av_textblock_section av-lbks6vkb-4790e205ad3489c04f90acb1269e0881 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Comparison of accelerator performance<\/h2>\n<\/div><\/section><br \/>\n<div class='avia-data-table-wrap av-3l9ztqr-01c0975c9921573b661f042dca2943a0 avia_responsive_table avia-table-2'><table  class='avia-table avia-data-table avia_pricing_default  avia-builder-el-22  el_after_av_textblock  el_before_av_textblock '  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/Table\" ><tbody><tr class=''><td class=''>Company<\/td><td class='avia-center-col'>NVIDIA<\/td><td class='avia-center-col'>NVIDIA<\/td><td class='avia-center-col'>AMD<\/td><td class='avia-center-col'>AMD<\/td><td class='avia-center-col'>Intel<\/td><td class='avia-center-col'>Groq<\/td><td class='avia-center-col'>Cerebras<\/td><td class='avia-center-col'>Huawei<\/td><\/tr><tr class=''><td class=''>Accelerator<\/td><td class='avia-center-col'>B300<\/td><td class='avia-center-col'>Vera Rubin (R100)<\/td><td class='avia-center-col'>MI455X<\/td><td class='avia-center-col'>MI430X<\/td><td class='avia-center-col'>Gaudi 3<\/td><td class='avia-center-col'>Groq LPU<\/td><td class='avia-center-col'>WSE-3<\/td><td class='avia-center-col'>Ascend 950PR<\/td><\/tr><tr class=''><td class=''>FP16\/BF16<\/td><td class='avia-center-col'>2,250 TFLOPs<\/td><td class='avia-center-col'>4,000 TFLOPs<\/td><td class='avia-center-col'>5,000 TFLOPs<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>459 \/ 1,835 TFLOPs<\/td><td class='avia-center-col'>188 TFLOPs<\/td><td class='avia-center-col'>125,000 TFLOPs<\/td><td class='avia-center-col'>500 TFLOPs<\/td><\/tr><tr class=''><td class=''>FP8<\/td><td class='avia-center-col'>4,500 TFLOPs<\/td><td class='avia-center-col'>17,500 TFLOPs<\/td><td class='avia-center-col'>20,100 TFLOPs<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>1,835 TFLOPs<\/td><td class='avia-center-col'>376 TFLOPs<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>1,000 TFLOPs<\/td><\/tr><tr class=''><td class=''>FP4\/INT4<\/td><td class='avia-center-col'>13,500 TFLOPs<\/td><td class='avia-center-col'>50,000 TFLOPs FP4I, 35,000 TFLOPs FP4T*<br \/>\n<\/td><td class='avia-center-col'>40,300 TFLOPs<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>156,250 TFLOPs<\/td><td class='avia-center-col'>1,560 TFLOPs<\/td><\/tr><tr class=''><td class=''>INT8<\/td><td class='avia-center-col'>187.5 TOPs<\/td><td class='avia-center-col'>250 TOPs<\/td><td class='avia-center-col'>5,000 TOPs<\/td><td class='avia-center-col'>TB\/A<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>750 TOPs<\/td><td class='avia-center-col'>N\/A<\/td><td class='avia-center-col'>N\/A<\/td><\/tr><\/tbody><\/table><\/div><br \/>\n<section  class='av_textblock_section av-msprxjp1-d59747708545f4a24f0c988871d9f060 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p style=\"font-size: 11;\">* FP4I refers to NVFP4 performance in terms of inference accuracy; FP4T refers to NVFP4 performance in terms of training.<\/p>\n<\/div><\/section><\/p><\/div>\n<div  class='flex_column av-iqvdar-5ea8c3ceaf2a1f77cb2d22cf47a31e53 av_one_full  avia-builder-el-24  el_after_av_one_full  el_before_av_hr  first flex_column_div  column-top-margin'     ><section  id=\"nvidia\"  class='av_textblock_section av-lbp9r0m4-d1ad78ede2e7a45844aaf439e1df8905 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>NVIDIA B300 \/ Vera Rubin (R100)<img loading=\"lazy\" decoding=\"async\" class=\"wp-image-110295 size-full alignright\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/01\/DGX_Vera_Rubin_400x300.png\" alt=\"NVIDIA DGX Vera Rubin Blade\" width=\"400\" height=\"300\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/01\/DGX_Vera_Rubin_400x300.png 400w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/01\/DGX_Vera_Rubin_400x300-300x225.png 300w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/h2>\n<p>The NVIDIA B300 (Blackwell Ultra) accelerator delivers the computing power needed for massively scaled systems designed for both training and inference of today\u2019s most complex AI models. The B300 is built on an optimized Blackwell architecture (using TSMC\u2019s 4NP process), which delivers multi-fold performance gains over the previous generation, Hopper, in a wide range of applications. With a massive 288 GB of HBM3e memory and bandwidth reaching 8 TB\/s, it serves as the ideal backbone for deploying large language models (LLMs) and massive datasets.<\/p>\n<p>In contrast, the Vera Rubin architecture with the R100 model represents not merely an evolution, but a completely new generational leap driven by the 3nm manufacturing process. Thanks to new computing engines, performance for AI applications is reaching entirely new levels while maintaining high energy efficiency. Furthermore, the Rubin R100 is the first on the market to feature revolutionary HBM4 memory with an incredible bandwidth of 22 TB\/s, which addresses the historically greatest weakness of AI accelerators: the so-called \u201cmemory wall\u201d (memory bottleneck).<\/p>\n<h3>LLM, Generative AI, Deep Learning, Machine Learning, Data Processing<\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-115125 alignright\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu.webp\" alt=\"Memory Access Speed: Vera Rubin vs. Blackwell\" width=\"627\" height=\"296\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu.webp 1999w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-300x142.webp 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-1030x486.webp 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-768x363.webp 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-1536x725.webp 1536w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-1500x708.webp 1500w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/memory-bandwidth-nvidia-rubin-gpu-705x333.webp 705w\" sizes=\"auto, (max-width: 627px) 100vw, 627px\" \/><\/p>\n<p>Both architectures represent the absolute cutting edge for solutions involving neural network training, massive data analytics, and the operation of Mixture-of-Experts (MoE) models, where extreme memory capacity and lightning-fast interconnections between individual nodes are critically important. A key innovation is full hardware support for 4-bit precision (FP4) computations, enabling the R100 to deliver up to 50 PFLOPS of inference throughput per card, which drastically reduces costs and accelerates the production deployment of AI.<\/p>\n<p>In addition, both the B300 and R100 take full advantage of the latest iterations of NVLink interconnect technology, which is key to scalability. While the B300 uses 5th-generation NVLink with a data rate of 1.8 TB\/s, the R100 pushes the boundaries with 6th-generation NVLink and a throughput of 3.6 TB\/s per GPU. With the help of advanced NVLink Switch systems, dozens of chips can be interconnected across entire racks to form a single massive logical unit. Combined with high-speed networking and NVIDIA MagnumIO software, these solutions enable seamless, lossless scaling from smaller enterprise clusters all the way up to exascale supercomputers.<\/p>\n<\/div><\/section><\/div>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-mspstonc-4144f3a2f89041fa82b1da2eca9104c7\">\n#top .hr.av-mspstonc-4144f3a2f89041fa82b1da2eca9104c7{\nmargin-top:50px;\nmargin-bottom:50px;\n}\n.hr.av-mspstonc-4144f3a2f89041fa82b1da2eca9104c7 .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-mspstonc-4144f3a2f89041fa82b1da2eca9104c7 hr-custom  avia-builder-el-26  el_after_av_one_full  el_before_av_one_full  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<div  class='flex_column av-o7vpdf-3b189c27a356058b978029b84095fef7 av_one_full  avia-builder-el-27  el_after_av_hr  el_before_av_hr  first flex_column_div  '     ><section  id=\"amd\"  class='av_textblock_section av-lbngq4jx-6cfcac5b386be203873d6879a67defb3 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>AMD Instinct MI455X<\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-115090\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-300x153.webp\" alt=\"AMD MI455X Announcement\" width=\"425\" height=\"216\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-300x153.webp 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-1030x524.webp 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-768x391.webp 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-1536x781.webp 1536w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-2048x1041.webp 2048w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-1500x763.webp 1500w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-gpu-705x359.webp 705w\" sizes=\"auto, (max-width: 425px) 100vw, 425px\" \/><\/p>\n<p>This AMD flagship for 2026, built on the new CDNA 5 architecture, is a direct response to NVIDIA\u2019s competing Rubin platform. The chip consists of 12 chiplets utilizing TSMC\u2019s advanced 2nm and 3nm manufacturing processes and contains a massive 320 billion transistors in total. The MI455X accelerator is designed primarily for large-scale server deployments; a typical example is the AMD Helios infrastructure, which combines a total of 72 of these cards into a single computing unit within a single rack.<\/p>\n<h3><img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-115092\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip-300x255.png\" alt=\"AMD Instinct MI455X Chip\" width=\"316\" height=\"269\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip-300x255.png 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip-1030x876.png 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip-768x653.png 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip-705x599.png 705w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-mi455x-chip.png 1200w\" sizes=\"auto, (max-width: 316px) 100vw, 316px\" \/> Leads the Pack in HBM4 Memory Capacity<\/h3>\n<p>A key competitive advantage of the MI455X is its memory subsystem. The card features an unprecedented 432 GB of next-generation HBM4 memory with a bandwidth reaching an incredible 23.3 TB\/s. In terms of capacity alone, it surpasses NVIDIA\u2019s current solutions (288 GB for the B300 and R100 chips) by a full 50%. This advantage plays a critical role in the inference and training of the largest language models, which can now fit much more easily into the memory of a single card or a small number of cards without the need for complex partitioning. Raw computational performance in AI operations peaks at 40 PFLOPS for the FP4 data format.<\/p>\n<h2>AMD Instinct MI430X<\/h2>\n<p>While the MI455X model is focused purely on maximum performance for generative artificial intelligence, the MI430X variant (which is expected to be fully deployed commercially in 2027) targets traditional HPC, national supercomputers, and scientific institutions. Although the card retains the massive 432 GB of HBM4 memory and high bandwidth, the internal architecture of its computing units differs in its primary focus.<\/p>\n<h3>Top Performance for Scientific Simulations (FP64)<\/h3>\n<p>A key feature of the MI430X is its optimization for FP64 (double-precision) computations, which are absolutely essential for complex physical simulations, climate modeling, and materials development. In this regard, the card achieves a hardware performance of 288 TFLOPS, overwhelmingly surpassing all available alternatives on the market. The goal of this solution is to enable institutions to run the most demanding scientific simulations while simultaneously training AI models directly on the generated data within a single unified ecosystem.<\/p>\n<\/div><\/section><\/div>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-msps9p7e-8f7d1400566ea3af7880e28a11cb48f2\">\n#top .hr.av-msps9p7e-8f7d1400566ea3af7880e28a11cb48f2{\nmargin-top:50px;\nmargin-bottom:0px;\n}\n.hr.av-msps9p7e-8f7d1400566ea3af7880e28a11cb48f2 .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-msps9p7e-8f7d1400566ea3af7880e28a11cb48f2 hr-custom  avia-builder-el-29  el_after_av_one_full  el_before_av_section  avia-builder-el-last  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3'  class='avia-section av-115tjeb-24609ef31e7031f53754f0cae2b5632d main_color avia-section-no-padding avia-no-border-styling  avia-builder-el-30  el_after_av_hr  el_before_av_hr  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n<div  class='flex_column av-14krjtf-bac881f6dec75f92d6a2fa068497bf59 av_one_full  avia-builder-el-31  el_before_av_one_full  avia-builder-el-first  first flex_column_div  '     ><section  id=\"intel\"  class='av_textblock_section av-vt9ycz-6a70a80a2a8f82edbbd85c6b38ad0ffc '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Intel Gaudi 3<img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-115052\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-300x184.png\" alt=\"Intel Gaudi 3 Accelerator\" width=\"435\" height=\"267\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-300x184.png 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-1030x633.png 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-768x472.png 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-1536x944.png 1536w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-1500x921.png 1500w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-705x433.png 705w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3.png 1571w\" sizes=\"auto, (max-width: 435px) 100vw, 435px\" \/><\/h2>\n<p>Intel\u2019s third-generation AI accelerator, Gaudi 3, represents a significant technological leap forward compared to their predecessor thanks to the transition to a 5nm manufacturing process. The card, built on the standardized OAM (Open Accelerator Module) format, is equipped with 64 tensor cores and eight specialized matrix multiplication engines. Memory capacity has increased to 128 GB of HBM2e with a bandwidth of 3.7 TB\/s, enabling the system to handle large language models much more smoothly.<\/p>\n<h3 style=\"padding-top: 20px;\">A cost-effective alternative for AI training and inference<\/h3>\n<p>While Gaudi 2 was compared to the NVIDIA A100, the goal of the Gaudi 3 generation is to compete with the NVIDIA H100. Although it lags slightly behind its main rival in raw computing power (reaching 1,835 TFLOPS for BF16\/FP8 operations), its main strength is cost-effectiveness. The chip is about half the price, yet delivers comparable results in a range of real-world AI applications, making it a highly attractive choice for building large-scale data centers and clusters with a focus on return on investment.<\/p>\n<\/div><\/section><\/div><div  class='flex_column av-15vk7yr-857615fecedef1c42445bfc9c4aa6dcf av_one_full  avia-builder-el-33  el_after_av_one_full  el_before_av_one_full  first no_margin flex_column_div  column-top-margin'     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-lbnn85bw-d05b21b7696550c1f93488ba0d224cc8\">\n.avia-image-container.av-lbnn85bw-d05b21b7696550c1f93488ba0d224cc8 img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-lbnn85bw-d05b21b7696550c1f93488ba0d224cc8 .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-lbnn85bw-d05b21b7696550c1f93488ba0d224cc8 av-styling- avia-align-center  avia-builder-el-34  el_before_av_codeblock  avia-builder-el-first '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-115058 avia-img-lazy-loading-not-115058 avia_image ' src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark.jpg\" alt='Benchmark Intel Gaudi 3' title='intel-gaudi-3-benchmark'  height=\"820\" width=\"1598\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark.jpg 1598w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-300x154.jpg 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-1030x529.jpg 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-768x394.jpg 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-1536x788.jpg 1536w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-1500x770.jpg 1500w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/intel-gaudi-3-benchmark-705x362.jpg 705w\" sizes=\"(max-width: 1598px) 100vw, 1598px\" \/><\/div><\/div><\/div><br \/>\n<\/p><\/div><div  class='flex_column av-m28s37-c27af93a5422852d16e7e9e9e7b3e62b av_one_full  avia-builder-el-36  el_after_av_one_full  avia-builder-el-last  first flex_column_div  column-top-margin'     ><section  class='av_textblock_section av-lbnpnqnv-baf6361137efbf8252ee7c64b114bb99 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h3>Integrated RoCEv2 Scaling<\/h3>\n<p>As with previous generations, the Gaudi platform\u2019s greatest strength lies in its network integration. Gaudi 3 features twenty-four integrated 200-gigabit RDMA over Converged Ethernet (RoCEv2) ports directly on the chip, which is twice the speed of Gaudi 2. This built-in connectivity completely eliminates the need for expensive external network switches for intra-node communication, and thanks to the Ethernet industry standard, customers can scale their computing clusters seamlessly from eight accelerators in a single rack up to massive systems with thousands of units.<\/p>\n<\/div><\/section><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_3'  class='main_color av_default_container_wrap container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-mspsuhz2-7528eddf9b868a8277a034cdf54ccab9\">\n#top .hr.av-mspsuhz2-7528eddf9b868a8277a034cdf54ccab9{\nmargin-bottom:0px;\n}\n.hr.av-mspsuhz2-7528eddf9b868a8277a034cdf54ccab9 .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-mspsuhz2-7528eddf9b868a8277a034cdf54ccab9 hr-custom  avia-builder-el-38  el_after_av_section  el_before_av_section  avia-builder-el-no-sibling  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4'  class='avia-section av-j9016cv-adad36c26d752ab25cdc5c765455cae9 main_color avia-section-no-padding avia-no-border-styling  avia-builder-el-39  el_after_av_hr  el_before_av_hr  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n<div  class='flex_column av-f7d619r-7f6be9a99940ae6ab65f388b1d43ecb0 av_one_full  avia-builder-el-40  el_before_av_one_half  avia-builder-el-first  first flex_column_div  '     ><section  id=\"groq\"  class='av_textblock_section av-msonxink-74ce820191b5a84625c8f6e8fc0f2cf2 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Groq LPU: A Revolution in Inference Speed<\/h2>\n<p>Although Groq had existed previously, it wasn\u2019t until the massive rise of generative AI that it definitively established itself among the key players in the HPC market. Its solution, known as the LPU (Language Processing Unit), represents a completely different approach to accelerating artificial intelligence than traditional graphics processing units (GPUs). As the name suggests, LPU chips are not primarily designed for the computationally intensive training of new neural networks, but focus purely on inference\u2014that is, running already trained large language models (LLMs) as quickly and efficiently as possible in real time.<\/p>\n<h3>The End of HBM Memory and Deterministic Architecture<\/h3>\n<p data-path-to-node=\"5\">The main difference from the competition lies in the memory architecture. Traditional accelerators from NVIDIA or AMD rely on external HBM memory. Although these memory modules are enormous and offer massive bandwidth, the constant transfer of data (model parameters) between the memory and the computing core causes an inevitable delay known as the \u201cmemory wall.\u201d Groq radically circumvents this problem by completely eliminating the need for traditional external memory.<\/p>\n<p data-path-to-node=\"6\">This LPU architecture (also known as the Tensor Streaming Processor) uses exclusively integrated on-chip SRAM, which is physically located right next to the computing units. The latest-generation Groq 3 LPU from 2026 features 500 MB of extremely fast memory per chip with a local bandwidth of an incredible 150 TB\/s. As a result, it delivers deterministic hardware capable of generating text or code at a rate of hundreds of tokens per second with virtually zero latency.<\/p>\n<h3 data-path-to-node=\"6\">Scaling for Real-Time AI<\/h3>\n<p>Since modern models with tens of billions of parameters obviously won\u2019t fit into a single chip\u2019s 500 MB of memory, the magic of the Groq LPU lies in its seamless interconnectivity. A standard computing node interconnects hundreds of these chips (typically 256 chips in a single rack) via a proprietary network. From the perspective of the software and compiler, the entire rack then behaves completely synchronously as a single massive processor. Optimized for the FP8 format, such a cluster achieves a performance of 315 PFLOPS, making it the uncompromising choice for deploying voice AI assistants, autonomous agents, and applications where immediate response is a critical factor.<\/p>\n<\/div><\/section><\/div><div  class='flex_column av-d3oqh2n-3b6fb1949de45d0a71550e26a3a72f89 av_one_half  avia-builder-el-42  el_after_av_one_full  el_before_av_one_half  first flex_column_div  column-top-margin'     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-msooqn7n-0f4ea39fe95e57703f8f436a0428b584\">\n.avia-image-container.av-msooqn7n-0f4ea39fe95e57703f8f436a0428b584 img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-msooqn7n-0f4ea39fe95e57703f8f436a0428b584 .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-msooqn7n-0f4ea39fe95e57703f8f436a0428b584 av-styling- avia-align-center  avia-builder-el-43  avia-builder-el-no-sibling '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-115105 avia-img-lazy-loading-not-115105 avia_image ' src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray.webp\" alt='Groq 3 LPU' title='NVIDIA Groq 3 LPX Compute Tray'  height=\"966\" width=\"1746\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray.webp 1746w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-300x166.webp 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-1030x570.webp 1030w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-768x425.webp 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-1536x850.webp 1536w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-1500x830.webp 1500w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/LPX02-Groq3LPX_Compute_Tray-705x390.webp 705w\" sizes=\"(max-width: 1746px) 100vw, 1746px\" \/><\/div><\/div><\/div><\/div><div  class='flex_column av-6933zu7-5f19dafb7c8b024b3bd3e3893cbfb486 av_one_half  avia-builder-el-44  el_after_av_one_half  avia-builder-el-last  flex_column_div  column-top-margin'     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-msoowxp7-ab0395b4ffb56801f807160292ca654c\">\n.avia-image-container.av-msoowxp7-ab0395b4ffb56801f807160292ca654c img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-msoowxp7-ab0395b4ffb56801f807160292ca654c .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-msoowxp7-ab0395b4ffb56801f807160292ca654c av-styling- avia-align-center  avia-builder-el-45  avia-builder-el-no-sibling '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-115210 avia-img-lazy-loading-not-115210 avia_image ' src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/groq.svg\" alt='Groq Logo' title='Groq Logo'  height=\"726\" width=\"1981\"  itemprop=\"thumbnailUrl\"  \/><\/div><\/div><\/div><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_4'  class='main_color av_default_container_wrap container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-mspt3u0o-7e7af831357db8d47ceeee6334ce76e0\">\n#top .hr.av-mspt3u0o-7e7af831357db8d47ceeee6334ce76e0{\nmargin-bottom:50px;\n}\n.hr.av-mspt3u0o-7e7af831357db8d47ceeee6334ce76e0 .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-mspt3u0o-7e7af831357db8d47ceeee6334ce76e0 hr-custom  avia-builder-el-46  el_after_av_section  el_before_av_one_full  avia-builder-el-first  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<div  class='flex_column av-w2qqvn-142a16617181ae5acd37cc1ba1537719 av_one_full  avia-builder-el-47  el_after_av_hr  el_before_av_hr  first flex_column_div  '     ><section  id=\"cerebras\"  class='av_textblock_section av-lbuphdn3-27c69fdc61e2b4b27f15a064da94000d '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>Cerebras WSE-3<\/h2>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-115065 size-medium alignright\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3-300x300.png\" alt=\"Cerebras WSE-3 Wafer-Scale System\" width=\"300\" height=\"300\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3-300x300.png 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3-80x80.png 80w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3-36x36.png 36w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3-180x180.png 180w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/cerebras-wse3.png 690w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>In the case of Cerebras, this is a truly unique piece of technology\u2014a gigantic chip the size of an entire silicon wafer with an area of 46,225 mm\u00b2. In the third generation of this accelerator, which uses TSMC\u2019s 5-nanometer manufacturing process, engineers have managed to pack 4 trillion transistors and 900,000 cores optimized for artificial intelligence.<\/p>\n<p><strong>The WSE<\/strong> (Wafer Scale Engine) concept offers significant advantages over traditional clustered systems. Since all computing power is concentrated on a single massive surface, communication paths between units are minimal, which significantly reduces latency compared to the standard interconnects that limit traditional graphics clusters. The chip achieves a peak AI performance of 125 petaFLOPS. At the same time, 44 GB of extremely fast SRAM memory is integrated onto the wafer itself, offering a massive data throughput of 21 petabytes per second.<\/p>\n<h3>Simplified Training of Gigantic Models<\/h3>\n<p>While in traditional GPU clusters, large language models must be distributed across thousands of cards in a highly complex manner that results in performance loss, the WSE-3 architecture (which forms the basis of CS-3 supercomputers) can seamlessly train AI models with up to 24 trillion parameters on a single system. For the most demanding operations and future models, the Cerebras solution allows up to 2,048 of these systems to be interconnected, creating an AI supercomputer with a staggering performance of 256 exaFLOPS.<\/p>\n<\/div><\/section><\/div>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-mspt4a56-ab94fa7e8e6a4b4fd521eea9ea151eee\">\n#top .hr.av-mspt4a56-ab94fa7e8e6a4b4fd521eea9ea151eee{\nmargin-top:30px;\nmargin-bottom:50px;\n}\n.hr.av-mspt4a56-ab94fa7e8e6a4b4fd521eea9ea151eee .hr-inner{\nwidth:100vw;\nborder-color:#e5f4ff;\n}\n<\/style>\n<div  class='hr av-mspt4a56-ab94fa7e8e6a4b4fd521eea9ea151eee hr-custom  avia-builder-el-49  el_after_av_one_full  el_before_av_one_full  hr-center hr-icon-no'><span class='hr-inner inner-border-av-border-thin'><span class=\"hr-inner-style\"><\/span><\/span><\/div>\n<div  class='flex_column av-8l1tq3z-8d33915d06e83d3a6daad240c736c408 av_one_full  avia-builder-el-50  el_after_av_hr  el_before_av_section  avia-builder-el-last  first flex_column_div  '     ><section  id=\"huawei\"  class='av_textblock_section av-msop5vk9-373357510552c51f4fd9b154fbf94e6e '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>The Chinese Market and Export Restrictions: The Absence of NVIDIA and the Rise of Domestic Chips<img loading=\"lazy\" decoding=\"async\" class=\" wp-image-115111 alignright\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/huwawei.png\" alt=\"Huawei Ascend Chip\" width=\"440\" height=\"249\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/huwawei.png 864w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/huwawei-300x169.png 300w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/huwawei-768x434.png 768w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/huwawei-705x398.png 705w\" sizes=\"auto, (max-width: 440px) 100vw, 440px\" \/><\/h2>\n<p>In recent years, the geopolitical situation has had a profound impact on the global market for HPC and AI accelerators. Due to strict export restrictions imposed by the U.S. government, NVIDIA (and other Western manufacturers) are now prohibited from supplying their most powerful chips to the Chinese market. While previously at least specially modified and downgraded models (such as the NVIDIA H20) were available on this market, current flagship models based on the Blackwell (B300) or Vera Rubin architectures are completely unavailable in China. Furthermore, in response to these sanctions, the Chinese government is actively pressuring local tech giants to completely cut themselves off from Western hardware.<\/p>\n<h3>Huawei Ascend 950PR: A New Chinese Flagship<\/h3>\n<p>This pressure created enormous opportunities for domestic manufacturers, and Huawei was the company that capitalized on them the most. In early 2026, it unveiled its new technological flagship\u2014the Da Vinci 3.0 architecture with the accelerator <strong data-path-to-node=\"13\" data-index-in-node=\"207\">Ascend 950PR<\/strong>. This chip replaces previous generations (910B\/910C) and is designed specifically for training and inference of the largest language models. Chinese tech giants such as ByteDance and Alibaba are already investing billions of dollars in these chips. A major breakthrough is Huawei\u2019s new CANN Next software stack, which emulates NVIDIA\u2019s CUDA environment directly at the hardware level. For Chinese AI labs, this greatly simplifies the transition, as they no longer need to go through the laborious process of rewriting millions of lines of legacy code.<\/p>\n<h3 data-path-to-node=\"4\">Production Limits and Catching Up to the West<\/h3>\n<p data-path-to-node=\"5\">Although development in China is proceeding at an unprecedented pace, hardware there continues to face physical and manufacturing limitations caused by the embargo on Western EUV lithography machines (from the Dutch company ASML). Production of the new Ascend 950PR chip is handled by the domestic foundry SMIC using its more advanced 5nm process (referred to as N+3). However, because it remains dependent on older DUV machines, it struggles with low efficiency and yield. Another difference is the absence of HBM3e\/HBM4 memory. Huawei therefore equips the chips with its proprietary memory called HiBL, which is cheaper to manufacture but does not achieve the same extreme bandwidth as Western standards.<\/p>\n<p data-path-to-node=\"5\">From an analytical standpoint, the Ascend 950PR still lags behind the top U.S. chips from NVIDIA and AMD in terms of raw performance. For example, for FP4 computations, the Ascend 950PR delivers around 1.56 PFLOPS, while the NVIDIA B300 achieves more than eight times that. Crucially, however, this hardware is more than sufficient for China\u2019s needs. Thanks to unlimited government funding, the low purchase price of the cards, and massive scaling (using its own high-speed LingQu interconnect network), Huawei can make up for the lack of performance per card simply by connecting thousands of them into giant clusters. For the local market, the Ascend 950 family thus represents a fully self-sufficient and highly functional ecosystem today.<\/p>\n<\/div><\/section><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_5'  class='avia-section av-2fx9flf-330b20e50bafb3a93aff5a64ea183558 main_color avia-section-default avia-no-border-styling  avia-builder-el-52  el_after_av_one_full  avia-builder-el-last  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-115263'><div class='entry-content-wrapper clearfix'>\n<section  class='av_textblock_section av-2ai9yz7-41829768f8693af36bb37f3595a9dc3c '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock h-decor'  itemprop=\"text\" ><h2>News<\/h2>\n<\/div><\/section>\n<div  class='flex_column av-1gketeb-290cb893e3afc580b80d626a6903173c av_one_full  avia-builder-el-54  el_after_av_textblock  avia-builder-el-last  post-slider-col3 first flex_column_div  column-top-margin'     ><p><div  data-slideshow-options=\"{&quot;animation&quot;:&quot;fade&quot;,&quot;autoplay&quot;:true,&quot;loop_autoplay&quot;:&quot;endless&quot;,&quot;interval&quot;:&quot;5&quot;,&quot;loop_manual&quot;:&quot;manual-endless&quot;,&quot;autoplay_stopper&quot;:false,&quot;noNavigation&quot;:false,&quot;show_slide_delay&quot;:90}\" class='avia-content-slider avia-content-slider-active avia-content-slider1 avia-content-slider-even  avia-builder-el-55  el_before_av_textblock  avia-builder-el-first  new-post-grid av-slideshow-ui av-control-default   av-no-slider-navigation av-slideshow-autoplay av-loop-endless av-loop-manual-endless '  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/Blog\" ><div class=\"avia-content-slider-inner\"><div class=\"slide-entry-wrap\"><article class='slide-entry flex_column  post-entry post-entry-115263 slide-entry-overview slide-loop-1 slide-parity-odd  av_one_fourth first real-thumbnail posttype-post post-format-standard'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><a href='https:\/\/mcomputers.cz\/en\/2026\/08\/10\/comparison-of-hpc-accelerators-2026\/' data-rel='slide-1' class='slide-image' title='Comparison of HPC Accelerators 2026'><img decoding=\"async\" fetchpriority=\"high\" width=\"710\" height=\"375\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-instinct-mi455x-die-710x375.webp\" class=\"wp-image-115225 avia-img-lazy-loading-not-115225 attachment-magazine size-magazine wp-post-image\" alt=\"Akceler\u00e1tor Amd Instinct MI455X\" srcset=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-instinct-mi455x-die-710x375.webp 710w, https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/amd-instinct-mi455x-die-800x423.webp 800w\" sizes=\"(max-width: 710px) 100vw, 710px\" \/><\/a><div class=\"slide-content\"><header class=\"entry-content-header\" aria-label=\"Slide: Comparison of HPC Accelerators 2026\"><h3 class='slide-entry-title entry-title '  itemprop=\"headline\" ><a href='https:\/\/mcomputers.cz\/en\/2026\/08\/10\/comparison-of-hpc-accelerators-2026\/' title='Comparison of HPC Accelerators 2026'>Comparison of HPC Accelerators 2026<\/a><\/h3><span class=\"av-vertical-delimiter\"><\/span><\/header><div class=\"slide-meta\"><time class='slide-meta-time updated'  itemprop=\"datePublished\" datetime=\"2026-08-10T09:47:50+01:00\" >10.8.2026<\/time><\/div><div class='slide-entry-excerpt entry-content'  itemprop=\"text\" >\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n<\/div><\/div><footer class=\"entry-footer\"><\/footer><span class='hidden'>\n\t\t\t\t<span class='av-structured-data'  itemprop=\"image\" itemscope=\"itemscope\" 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datetime=\"2026-08-10T09:47:50+01:00\" >2026-08-10 09:47:50<\/span><span class='av-structured-data'  itemprop=\"dateModified\" itemtype=\"https:\/\/schema.org\/dateModified\" >2026-08-13 13:10:46<\/span><span class='av-structured-data'  itemprop=\"mainEntityOfPage\" itemtype=\"https:\/\/schema.org\/mainEntityOfPage\" ><span itemprop='name'>Comparison of HPC Accelerators 2026<\/span><\/span><\/span><\/article><article class='slide-entry flex_column  post-entry post-entry-115025 slide-entry-overview slide-loop-2 slide-parity-even  av_one_fourth  real-thumbnail posttype-post post-format-standard'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><a href='https:\/\/mcomputers.cz\/en\/2026\/08\/10\/m-computers-lenovo-padel-2026\/' data-rel='slide-1' class='slide-image' title='M Computers \u00d7 Lenovo: A Partnership in Action on the Court'><img decoding=\"async\" fetchpriority=\"high\" width=\"710\" height=\"375\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/Padel-Lenovo-x-M-Computers-710x375.png\" class=\"wp-image-114988 avia-img-lazy-loading-not-114988 attachment-magazine size-magazine wp-post-image\" alt=\"\" \/><\/a><div class=\"slide-content\"><header class=\"entry-content-header\" aria-label=\"Slide: M Computers \u00d7 Lenovo: A Partnership in Action on the Court\"><h3 class='slide-entry-title entry-title '  itemprop=\"headline\" ><a href='https:\/\/mcomputers.cz\/en\/2026\/08\/10\/m-computers-lenovo-padel-2026\/' title='M Computers \u00d7 Lenovo: A Partnership in Action on the Court'>M Computers \u00d7 Lenovo: A Partnership in Action on the Court<\/a><\/h3><span class=\"av-vertical-delimiter\"><\/span><\/header><div class=\"slide-meta\"><time class='slide-meta-time updated'  itemprop=\"datePublished\" datetime=\"2026-08-10T08:17:37+01:00\" >10.8.2026<\/time><\/div><div class='slide-entry-excerpt entry-content'  itemprop=\"text\" >\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n<\/div><\/div><footer class=\"entry-footer\"><\/footer><span class='hidden'>\n\t\t\t\t<span class='av-structured-data'  itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" >\n\t\t\t\t\t\t<span itemprop='url'>https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/08\/Padel-Lenovo-x-M-Computers.png<\/span>\n\t\t\t\t\t\t<span itemprop='height'>731<\/span>\n\t\t\t\t\t\t<span itemprop='width'>1030<\/span>\n\t\t\t\t<\/span>\n\t\t\t\t<span class='av-structured-data'  itemprop=\"publisher\" itemtype=\"https:\/\/schema.org\/Organization\" itemscope=\"itemscope\" >\n\t\t\t\t\t\t<span itemprop='name'>Eli\u0161ka Pechancov\u00e1<\/span>\n\t\t\t\t\t\t<span itemprop='logo' itemscope itemtype='https:\/\/schema.org\/ImageObject'>\n\t\t\t\t\t\t\t<span 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class=\"av-vertical-delimiter\"><\/span><\/header><div class=\"slide-meta\"><time class='slide-meta-time updated'  itemprop=\"datePublished\" datetime=\"2026-07-30T10:49:25+01:00\" >30.7.2026<\/time><\/div><div class='slide-entry-excerpt entry-content'  itemprop=\"text\" >\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n<\/div><\/div><footer class=\"entry-footer\"><\/footer><span class='hidden'>\n\t\t\t\t<span class='av-structured-data'  itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" >\n\t\t\t\t\t\t<span itemprop='url'>https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/Vltava-2026.png<\/span>\n\t\t\t\t\t\t<span itemprop='height'>731<\/span>\n\t\t\t\t\t\t<span itemprop='width'>1030<\/span>\n\t\t\t\t<\/span>\n\t\t\t\t<span class='av-structured-data'  itemprop=\"publisher\" itemtype=\"https:\/\/schema.org\/Organization\" itemscope=\"itemscope\" >\n\t\t\t\t\t\t<span itemprop='name'>Eli\u0161ka Pechancov\u00e1<\/span>\n\t\t\t\t\t\t<span itemprop='logo' itemscope itemtype='https:\/\/schema.org\/ImageObject'>\n\t\t\t\t\t\t\t<span itemprop='url'>http:\/\/mcomputers.cz\/wp-content\/uploads\/2024\/12\/obrazek_2024-12-03_164614578-e1733305217994.png<\/span>\n\t\t\t\t\t\t<\/span>\n\t\t\t\t<\/span><span class='av-structured-data'  itemprop=\"author\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/Person\" ><span itemprop='name'>Eli\u0161ka Pechancov\u00e1<\/span><\/span><span class='av-structured-data'  itemprop=\"datePublished\" datetime=\"2026-08-10T09:47:50+01:00\" >2026-07-30 10:49:25<\/span><span class='av-structured-data'  itemprop=\"dateModified\" itemtype=\"https:\/\/schema.org\/dateModified\" >2026-07-30 12:05:25<\/span><span class='av-structured-data'  itemprop=\"mainEntityOfPage\" itemtype=\"https:\/\/schema.org\/mainEntityOfPage\" ><span itemprop='name'>Company Canoeing Trip on the Vltava<\/span><\/span><\/span><\/article><article class='slide-entry flex_column  post-entry post-entry-114318 slide-entry-overview slide-loop-4 slide-parity-even  post-entry-last  av_one_fourth  real-thumbnail posttype-post post-format-standard'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><a href='https:\/\/mcomputers.cz\/en\/2026\/07\/14\/m-computers-sponsored-the-3rd-lenovoshop-summer-cup\/' data-rel='slide-1' class='slide-image' title='M Computers Sponsored the 3rd Lenovoshop Summer Cup'><img decoding=\"async\" fetchpriority=\"high\" width=\"710\" height=\"375\" src=\"https:\/\/mcomputers.cz\/wp-content\/uploads\/2026\/07\/Lenovoshop-pohar-2026_nahled-710x375.png\" class=\"wp-image-114328 avia-img-lazy-loading-not-114328 attachment-magazine size-magazine wp-post-image\" alt=\"\" \/><\/a><div class=\"slide-content\"><header class=\"entry-content-header\" aria-label=\"Slide: M Computers Sponsored the 3rd Lenovoshop Summer Cup\"><h3 class='slide-entry-title entry-title '  itemprop=\"headline\" ><a 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class='av-structured-data'  itemprop=\"mainEntityOfPage\" itemtype=\"https:\/\/schema.org\/mainEntityOfPage\" ><span itemprop='name'>M Computers Sponsored the 3rd Lenovoshop Summer Cup<\/span><\/span><\/span><\/article><\/div><\/div><\/div><br \/>\n<section  class='av_textblock_section av-psqln7-55710d2cef64e934a839659da9257874 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p style=\"text-align: right;\"><a href=\"https:\/\/mcomputers.cz\/en\/news\/\">View more news<\/a><\/p>\n<\/div><\/section><\/p><\/div>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":18,"featured_media":115225,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[306,200,75,366],"tags":[145,344,85,84,88,116],"class_list":["post-115263","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-amd-en","category-intel-en","category-news","category-nvidia-en","tag-ai-en","tag-amd-en-2","tag-high-performance-computing-en","tag-hpc-en","tag-intel-en","tag-nvidia-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.2 (Yoast SEO v28.2) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Comparison of HPC Accelerators 2026 &#8211; M Computers s.r.o.<\/title>\n<meta name=\"description\" content=\"Every year there are new accelerators for HPC and AI, ML and DL application development. 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