{"id":12691,"date":"2026-08-18T22:14:41","date_gmt":"2026-08-18T22:14:41","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/draco-4x-h200-nvl-ai-server\/"},"modified":"2026-08-18T23:24:42","modified_gmt":"2026-08-18T23:24:42","slug":"draco-4x-h200-nvl-ai-server","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/draco-4x-h200-nvl-ai-server\/","title":{"rendered":"DRACO 4\u00d7 H200 NVL AI Server"},"content":{"rendered":"<p><strong>NVLink bandwidth in a rack you already have.<\/strong> Four NVIDIA H200 NVL cards &mdash; 564&nbsp;GB of HBM3e &mdash; bridged 4-way by NVLink in an air-cooled 4U chassis. The practical way to get true multi-GPU interconnect without an SXM baseboard, a CDU, or a facility water loop.<\/p>\n<h3>Key highlights<\/h3>\n<ul>\n<li><strong>4\u00d7 NVIDIA H200 NVL 141GB HBM3e<\/strong> \u2014 <strong>564 GB<\/strong> of high-bandwidth memory.<\/li>\n<li><strong>4-way NVLink bridge<\/strong> \u2014 GPU-to-GPU bandwidth far beyond PCIe peer-to-peer.<\/li>\n<li><strong>Air-cooled 4U<\/strong>, standard rack, standard PDU \u2014 installable in an existing server room.<\/li>\n<li><strong>512 GB DDR5 ECC<\/strong> on a dual-Xeon host with 2\u00d7 100GbE and BMC\/Redfish.<\/li>\n<li>Runs the <strong>same CUDA stack<\/strong> as SXM nodes \u2014 no software migration when you scale.<\/li>\n<li>PCIe serviceability: cards are <strong>field-replaceable individually<\/strong>, unlike an SXM baseboard.<\/li>\n<li>On-premises and <strong>DPDP-aligned<\/strong>; suitable for air-gapped deployment.<\/li>\n<\/ul>\n<h3>AI workload fit<\/h3>\n<ul>\n<li>Multi-GPU <strong>training<\/strong> and full fine-tuning at 70B\u2013180B.<\/li>\n<li>Long-context <strong>inference<\/strong> where HBM capacity is the binding constraint.<\/li>\n<li>Production <strong>RAG<\/strong> and retrieval services.<\/li>\n<li><strong>HPC &amp; AI<\/strong> converged workloads.<\/li>\n<li><strong>Agentic AI<\/strong> and <strong>generative AI<\/strong> back-ends.<\/li>\n<li><strong>Sovereign AI<\/strong> deployments in facilities that cannot support liquid cooling.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>The honest middle of the server range. H200 NVL is the <strong>PCIe<\/strong> form of H200, bridged in pairs or quads by <strong>NVLink<\/strong>. It matters because it delivers 141&nbsp;GB of HBM3e per GPU and NVLink-class GPU-to-GPU bandwidth into an <strong>air-cooled, standard-rack<\/strong> chassis &mdash; no SXM baseboard, no NVSwitch, no mandatory liquid loop. For a great many Indian server rooms that is the difference between a system that can be installed and one that cannot. Choose NVL over SXM when the facility, the serviceability model, or the budget rules out an eight-GPU liquid-cooled node \u2014 and accept that peak multi-node training throughput belongs to SXM.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>Public sector &amp; sovereign:<\/strong> NVLink-class capability in government facilities without water.<\/li>\n<li><strong>BFSI &amp; HFT:<\/strong> model training and low-latency inference inside the bank&#8217;s own DC.<\/li>\n<li><strong>Healthcare &amp; life sciences:<\/strong> imaging and genomics workloads under residency rules.<\/li>\n<li><strong>Research &amp; education:<\/strong> departmental training capability on an ordinary power budget.<\/li>\n<li><strong>Manufacturing:<\/strong> plant-side training and inference without a datacenter build.<\/li>\n<\/ul>\n<h3>Performance &amp; how to be sure<\/h3>\n<p>H200 NVL is capacity- and bandwidth-led rather than a peak-FLOPS play: 141 GB per GPU with NVLink bridging is what makes 70B\u2013180B training and long-context serving practical in an air-cooled box. Rather than quote a tokens\/sec figure that will not match your workload, RDP offers a <strong>&ldquo;benchmark your model&rdquo;<\/strong> session: bring the model, precision and context length you actually intend to run, and we will validate it on this exact configuration before you commit.<\/p>\n<h3>Series &amp; upgrade path<\/h3>\n<p>Below: the air-cooled <strong>RTX PRO 6000<\/strong> servers (inference\/LoRA-led, no NVLink). Beside it: <strong>8\u00d7 H200 NVL<\/strong> for double the density. Above: <strong>4\u00d7 and 8\u00d7 H200\/B200\/B300 SXM<\/strong> nodes with NVSwitch, then rack-scale GB300. Identical CUDA and serving stack throughout.<\/p>\n<h3>On-prem vs cloud (TCO)<\/h3>\n<p>For sustained daily AI work this configuration removes per-GPU-hour billing, queueing for scarce instances, and egress charges on your own data &mdash; and keeps everything on-premises for DPDP and data-residency obligations. Cloud still wins for burst capacity and one-off very large training runs; on-prem wins on sustained utilisation, control and predictable INR capital cost. We model the crossover with your actual usage rather than assert it.<\/p>\n<h3>Software &amp; day-one readiness<\/h3>\n<p>Ships workload-ready: Ubuntu LTS or RHEL, NVIDIA driver + CUDA + cuDNN, container runtime, Kubernetes\/Slurm integration. Standard serving stacks (vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo) supported, and NVIDIA AI Enterprise licensing can be bundled on request.<\/p>\n<h3>Power, thermal &amp; acoustics<\/h3>\n<p>4U air-cooled chassis with redundant PSUs on standard rack PDU feeds. No CDU, no facility water \u2014 a rack thermal survey is still recommended before install. <em>Exact wattage, BTU and dB(A) figures come from RDP bench measurement rather than estimates &mdash; ask for the site-readiness sheet with your quote.<\/em><\/p>\n<h3>Deployment, warranty &amp; support<\/h3>\n<p>Built to order by RDP Technologies. Supplied with GST invoice (HSN 8471), pan-India onsite support, and availability through GeM for public-sector procurement. Built to order \u2014 typically 8\u201310 weeks, subject to GPU allocation.<\/p>\n<h3>Why RDP<\/h3>\n<p>RDP Technologies is a Make-in-India OEM with 14+ years and 300,000+ units shipped, supplying AI infrastructure from desk-side systems to rack-scale AI factories &mdash; with predictable INR pricing, GST invoicing and pan-India onsite service.<\/p>\n<h3>Buy with confidence<\/h3>\n<p>Use <strong>Request a Quote<\/strong> to reach an RDP solution architect for sizing, a benchmark-your-model session, financing options and a delivery plan. No obligation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dual Xeon \u00b7 512GB DDR5 ECC \u00b7 4-way NVLink bridge \u00b7 4U rack \u00b7 air-cooled<\/p>\n","protected":false},"featured_media":2029,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"DRACO 4\u00d7 H200 NVL AI Server \u2014 NVLink PCIe, Air-Cooled 4U | RDP GPU Mart","rank_math_description":"Four NVIDIA H200 NVL PCIe GPUs with 4-way NVLink bridge and 564GB HBM3e in an air-cooled 4U: 70B\u2013180B training and inference on-premises. Request a quote from RDP GPU Mart.","_hermes_jsonld":""},"product_brand":[],"product_cat":[18],"product_tag":[],"class_list":["post-12691","product","type-product","status-publish","has-post-thumbnail","product_cat-gpu-servers","pa_form-factor-4u","pa_gpu-model-nvidia-h200-nvl","pa_industry-bfsi-hft","pa_industry-healthcare-life-sciences","pa_industry-manufacturing-industrial","pa_industry-public-sector-sovereign-ai","pa_industry-research-higher-education","pa_series-draco","pa_use-case-agentic-ai","pa_use-case-fine-tuning","pa_use-case-generative-ai","pa_use-case-hpc-ai","pa_use-case-inference","pa_use-case-llm-training","pa_use-case-rag","pa_use-case-sovereign-ai","pa_workload-fit-h200-nvl-inference-fine-tune-node","first","instock","taxable","shipping-taxable","product-type-external"],"_links":{"self":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product\/12691","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/types\/product"}],"replies":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/comments?post=12691"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media\/2029"}],"wp:attachment":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media?parent=12691"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_brand?post=12691"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_cat?post=12691"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_tag?post=12691"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}