{"id":250,"date":"2025-10-25T19:18:37","date_gmt":"2025-10-25T19:18:37","guid":{"rendered":"https:\/\/pckumar.in\/datacenters\/?page_id=250"},"modified":"2026-06-08T16:02:43","modified_gmt":"2026-06-08T16:02:43","slug":"nvidia-gb300-nvl72","status":"publish","type":"post","link":"https:\/\/pckumar.in\/datacenters\/nvidia-gb300-nvl72\/","title":{"rendered":"Nvidia GB300 NVL72"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”Header” _builder_version=”4.27.4″ background_image=”https:\/\/pckumar.in\/datacenters\/wp-content\/uploads\/2025\/10\/rtx-ai-workstations-ai-development-ari.jpeg” parallax=”on” custom_margin=”|||” custom_padding=”12vw|0px|0|0px|false|false” global_colors_info=”{}”][et_pb_row column_structure=”2_3,1_3″ padding_top_bottom_link_1=”false” padding_left_right_link_1=”true” _builder_version=”4.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” max_width=”1160px” custom_margin=”|||||false” custom_padding=”27px|0px|0|0px|false|false” use_custom_width=”on” custom_width_px=”1160px” global_colors_info=”{}”][et_pb_column type=”2_3″ _builder_version=”4.16″ background_color=”#ffffff” custom_padding=”40px|40px|0px|40px” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.27.4″ text_font=”||||||||” ul_font=”||||||||” ol_font=”||||||||” header_font=”Playfair Display|700|||||||” header_font_size=”48px” header_line_height=”1.5em” header_2_font=”||||||||” header_3_font=”Rubik|500||on|||||” header_3_text_color=”#098cf2″ header_3_font_size=”14px” header_3_letter_spacing=”2px” header_3_line_height=”2em” header_4_font=”||||||||” header_5_font=”||||||||” header_6_font=”||||||||” header_font_size_tablet=”38px” header_font_size_phone=”28px” header_font_size_last_edited=”on|phone” locked=”off” global_colors_info=”{}”]<\/p>\n

Nvidia GB300 NVL72<\/h1>\n

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\u00a0 \u00a0 \u00a0 Nvidia GB300 NVL72<\/h2>\n

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Designed for AI Reasoning Performance<\/h2>\n<\/div>\n<\/div>\n<\/div>\n
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The NVIDIA GB300 NVL72 features a fully liquid-cooled, rack-scale design that unifies 72\u00a0<\/span>NVIDIA Blackwell Ultra\u00a0<\/span>GPUs and 36 Arm\u00ae-based\u00a0<\/span>NVIDIA Grace\u2122 CPUs\u00a0<\/span>in a single platform optimized for test-time scaling inference.\u00a0<\/span>AI factories\u00a0<\/span>powered with the GB300 NVL72 using NVIDIA Quantum-X800 InfiniBand or Spectrum\u2122-X Ethernet paired with ConnectX\u00ae-8 SuperNICS provide a 50x higher output for reasoning model inference compared to the\u00a0<\/span>NVIDIA Hopper\u2122 platform.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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NVIDIA GB300 NVL72 Specifications<\/th>\n<\/tr>\n<\/thead>\n
Configuration<\/td>\n72 NVIDIA Blackwell Ultra GPUs, 36 NVIDIA Grace CPUs<\/td>\n<\/tr>\n
NVLink Bandwidth<\/td>\n130 TB\/s<\/td>\n<\/tr>\n
Fast Memory<\/td>\nUp to 40 TB<\/td>\n<\/tr>\n
GPU Memory | Bandwidth<\/td>\nUp to 21 TB | Up to 576 TB\/s<\/td>\n<\/tr>\n
CPU Memory | Bandwidth<\/td>\nUp to 18 TB SOCAMM with LPDDR5X | Up to 14.3 TB\/s<\/td>\n<\/tr>\n
CPU Core Count<\/td>\n2,592 Arm Neoverse V2 cores<\/td>\n<\/tr>\n
FP4 Tensor Core<\/td>\n1,400 | 1,100\u00b2 PFLOPS<\/td>\n<\/tr>\n
FP8\/FP6 Tensor Core<\/td>\n720 PFLOPS<\/td>\n<\/tr>\n
INT8 Tensor Core<\/td>\n23 PFLOPS<\/td>\n<\/tr>\n
FP16\/BF16 Tensor Core<\/td>\n360 PFLOPS<\/td>\n<\/tr>\n
TF32 Tensor Core<\/td>\n180 PFLOPS<\/td>\n<\/tr>\n
FP32<\/td>\n6 PFLOPS<\/td>\n<\/tr>\n
FP64 \/ FP64 Tensor Core<\/td>\n100 TFLOPS<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Nvidia GB300 NVL72\u00a0 \u00a0 \u00a0 Nvidia GB300 NVL72   Designed for AI Reasoning Performance The NVIDIA GB300 NVL72 features a fully liquid-cooled, rack-scale design that unifies 72\u00a0NVIDIA Blackwell Ultra\u00a0GPUs and 36 Arm\u00ae-based\u00a0NVIDIA Grace\u2122 CPUs\u00a0in a single platform optimized for test-time scaling inference.\u00a0AI factories\u00a0powered with the GB300 NVL72 using NVIDIA Quantum-X800 InfiniBand or Spectrum\u2122-X Ethernet paired […]<\/p>\n","protected":false},"author":3,"featured_media":95,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"2880","footnotes":""},"categories":[26,6],"tags":[],"class_list":["post-250","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-networking","category-nvidia"],"_links":{"self":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/posts\/250","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/comments?post=250"}],"version-history":[{"count":7,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/posts\/250\/revisions"}],"predecessor-version":[{"id":3433,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/posts\/250\/revisions\/3433"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/media\/95"}],"wp:attachment":[{"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/media?parent=250"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/categories?post=250"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/pckumar.in\/datacenters\/wp-json\/wp\/v2\/tags?post=250"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}