The QUASAR 4\u00d7 RTX PRO 6000 Blackwell GPU Server is a Rack 4U rack server built to bring inference into your own data centre. 4 RTX PRO 6000 Blackwell Server Edition GPUs deliver 384 GB GDDR7 of high-bandwidth GPU memory in a dense, serviceable chassis \u2014 sized to serve 70B+-class models and host many models at once, behind your firewall, in INR, on a GST invoice.<\/p>\n
Engineered for AI platform and MLOps teams standardising production inference on owned infrastructure, it pairs the GPUs with a 2\u00d7 Intel Xeon 6 host, 1 TB DDR5 ECC and 16 TB NVMe, with redundant power and full BMC\/IPMI remote management \u2014 a production node that racks and runs, not a repurposed desktop.<\/p>\n
This sits at the deploy-and-serve<\/strong> stage of the AI lifecycle. With 384 GB GDDR7 of GPU memory, a dense PCIe layout, a 2\u00d7 Intel Xeon 6 host and fast NVMe, it is sized to sustain<\/strong> production inference traffic with predictable latency \u2014 where renting equivalent cloud GPUs around the clock becomes the dominant line in an AI budget.<\/p>\n We don’t publish inflated peak numbers. The honest picture: 384 GB GDDR7 of GPU memory across 4 GPUs is sized to serve 70B+-class models and many concurrent smaller models on-prem. Want certainty? Request a free benchmark of your models and request mix on this exact configuration before you buy<\/strong> \u2014 we’ll send back real tokens\/sec, concurrency and latency for your workload.<\/p>\n For sustained inference, owning beats renting: 4 continuously-running cloud GPUs of this class add up fast, and on-prem removes egress fees and keeps data and weights in-house. RDP pricing is fixed in INR with a GST input-credit-eligible invoice \u2014 ask for a 3-year TCO comparison<\/strong> against your current cloud spend.<\/p>\n Ships pre-configured to serve<\/strong>: NVIDIA driver, CUDA, cuDNN, NCCL, Docker and NVIDIA Container Toolkit, with PyTorch, vLLM \/ Triton \/ TensorRT-LLM on Ubuntu LTS. Optional Slurm\/Kubernetes, managed AI-stack and observability setup available.<\/p>\n A Rack 4U air-cooled node with redundant PSUs and substantial power draw \u2014 specify rack power and cooling capacity; liquid-cooling available on request. (Exact PSU rating, BTU, airflow and rack-depth figures confirmed on the build sheet.)<\/em> BMC\/IPMI provides remote power, console and health monitoring.<\/p>\n 14 years of Make-in-India infrastructure and 300,000+ devices shipped<\/strong>. Indian OEM, INR pricing, GST tax invoice (HSN 8471), pan-India onsite engineers, GeM availability, and DPDP \/ sovereign-AI-ready deployment.<\/p>\n This is a production inference server, made to order \u2014 talk to an RDP solution architect<\/strong>, get a configuration and 3-year TCO tailored to your workload, and benchmark your own models on it before you commit.<\/strong> Request a quote to begin.<\/p>\n","protected":false},"excerpt":{"rendered":" 2\u00d7 Intel Xeon 6 \u00b7 1 TB DDR5 ECC \u00b7 16 TB NVMe \u00b7 4U rack<\/p>\n","protected":false},"featured_media":2259,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"QUASAR 4\u00d7 RTX PRO 6000 Blackwell GPU Server \u2014 2\u00d7 Intel Xeon 6, 1 TB DDR5 ECC, 384 GB GDDR7 GPU | RDP GPU Mart","rank_math_description":"On-prem RTX PRO 6000 Blackwell GPU server \u2014 4\u00d7 RTX PRO 6000 Blackwell (384 GB GDDR7), 2\u00d7 Intel Xeon 6, 1 TB DDR5 ECC, 16 TB NVMe. Serve 70B+-class models in your own data centre. Make-in-India, GST invoice, pan-India onsite. Request a quote.","_hermes_jsonld":""},"product_brand":[],"product_cat":[18],"product_tag":[83],"class_list":["post-71","product","type-product","status-publish","has-post-thumbnail","product_cat-gpu-servers","product_tag-ready-to-buy","pa_form-factor-rack","pa_gpu-model-nvidia-rtx-pro-6000-blackwell","pa_industry-automotive-mobility","pa_industry-bfsi-hft","pa_industry-defence-aerospace","pa_industry-enterprise-gccs","pa_industry-healthcare-life-sciences","pa_industry-manufacturing-industrial","pa_industry-media-gaming-entertainment","pa_industry-neocloud","pa_industry-public-sector-sovereign-ai","pa_industry-research-higher-education","pa_industry-retail-ecommerce","pa_industry-telecom-5g","pa_series-quasar","pa_use-case-agentic-ai","pa_use-case-computer-vision","pa_use-case-generative-ai","pa_use-case-inference","pa_use-case-llm-training","pa_use-case-fine-tuning","pa_use-case-nlp-speech","pa_use-case-rag","pa_workload-fit-inference-at-scale-fine-tuning","first","onbackorder","taxable","shipping-taxable","product-type-simple"],"_links":{"self":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product\/71","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=71"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media\/2259"}],"wp:attachment":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media?parent=71"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_brand?post=71"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_cat?post=71"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_tag?post=71"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Industry use cases<\/h3>\n
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Performance \u2014 and how to be sure<\/h3>\n
Series & upgrade path<\/h3>\n
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On-prem vs cloud \u2014 the TCO case<\/h3>\n
Software & day-one readiness<\/h3>\n
Power, cooling & rack integration<\/h3>\n
Deployment, warranty & support<\/h3>\n
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Why RDP<\/h3>\n
Buy with confidence<\/h3>\n