{"id":12611,"date":"2026-08-18T16:11:34","date_gmt":"2026-08-18T16:11:34","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/quasar-2x-rtx-pro-4500-aidaptiv-workstation\/"},"modified":"2026-08-18T23:24:41","modified_gmt":"2026-08-18T23:24:41","slug":"quasar-2x-rtx-pro-4500-aidaptiv-workstation","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/quasar-2x-rtx-pro-4500-aidaptiv-workstation\/","title":{"rendered":"QUASAR 2\u00d7 RTX PRO 4500 aiDAPTIV+ Workstation"},"content":{"rendered":"<p><strong>Two GPUs, 70B-class models, and none of it leaves your building.<\/strong> Dual NVIDIA RTX PRO 4500 Blackwell cards with a 1&nbsp;TB aiDAPTIV+ NVMe cache take a team from experimenting on 13B models to fine-tuning the 34B&ndash;70B class that most production Indian enterprise workloads actually settle on.<\/p>\n<h3>Key highlights<\/h3>\n<ul>\n<li><strong>2\u00d7 NVIDIA RTX PRO 4500 Blackwell 32GB<\/strong> \u2014 64 GB aggregate VRAM for model-parallel work.<\/li>\n<li><strong>1 TB aiDAPTIV+ cache<\/strong> (U.2 + M.2 enterprise NVMe) \u2014 the difference between &#8220;won&#8217;t load&#8221; and &#8220;runs&#8221;.<\/li>\n<li><strong>34B\u201370B fine-tuning<\/strong> with LoRA\/QLoRA, plus BF16\/INT4 inference.<\/li>\n<li><strong>256 GB DDR5 ECC RDIMM<\/strong> on an Intel Xeon w7 platform \u2014 real data-prep headroom.<\/li>\n<li><strong>4 TB NVMe<\/strong> for datasets, checkpoints and multiple model versions.<\/li>\n<li>Desk-side or small server-room footprint \u2014 <strong>no rack or facility cooling required<\/strong>.<\/li>\n<li>DPDP and data-residency preserved by design: <strong>the data never crosses your boundary<\/strong>.<\/li>\n<\/ul>\n<h3>AI workload fit<\/h3>\n<ul>\n<li><strong>Fine-tuning<\/strong> 34B\u201370B models (LoRA\/QLoRA) on proprietary corpora.<\/li>\n<li>Production <strong>inference<\/strong> for a department or business unit.<\/li>\n<li><strong>RAG<\/strong> over large private document estates.<\/li>\n<li><strong>Agentic AI<\/strong> workflows with tool use and multi-step reasoning.<\/li>\n<li><strong>Generative AI<\/strong>, <strong>computer vision<\/strong> and <strong>NLP &amp; speech<\/strong> workloads.<\/li>\n<li><em>Not<\/em> for foundation-model pretraining \u2014 step up to an RDP GPU server.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>The workhorse rung. Most organisations discover their real requirement is a well-tuned 34B\u201370B model on their own data rather than a frontier model on someone else&#8217;s cloud &mdash; this is the machine built for exactly that. aiDAPTIV+ extends usable model memory onto high-endurance enterprise NVMe, so a model class that would normally demand far more GPUs runs on the GPUs you actually own. It is a <strong>capacity<\/strong> technology, not a bandwidth one &mdash; streaming offload is tuned for inference and parameter-efficient fine-tuning (LoRA\/QLoRA), and the final numbers are confirmed in a scoped proof-of-concept, not promised on a datasheet.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>BFSI:<\/strong> risk, fraud and document-intelligence models tuned on in-house data.<\/li>\n<li><strong>Healthcare &amp; life sciences:<\/strong> clinical language models under residency obligations.<\/li>\n<li><strong>Manufacturing:<\/strong> vision QC and predictive-maintenance models trained on plant data.<\/li>\n<li><strong>Enterprise &amp; GCCs:<\/strong> a shared team box for AI platform and applied-AI groups.<\/li>\n<li><strong>Research &amp; education:<\/strong> lab-scale fine-tuning without competing for cluster time.<\/li>\n<\/ul>\n<h3>Performance &amp; how to be sure<\/h3>\n<p>With 64 GB of aggregate VRAM plus a 1 TB NVMe cache, the practical ceiling is set by memory capacity and offload streaming rather than compute &mdash; which is why we size it against your model and precision rather than a benchmark chart. 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><strong>QUASAR<\/strong> is the performance tier. Below it sits the <strong>CARINA 1\u00d7 RTX PRO 5000<\/strong> (13B\u201334B); above it the <strong>QUASAR 2\u00d7 RTX PRO 5000<\/strong> (70B) and the <strong>DRACO<\/strong> workstations (90B\u2013180B), then RDP GPU servers for 180B+ and true multi-GPU training. Identical software 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, and the aiDAPTIV+ memory-management layer, which is PyTorch-compliant and needs <strong>no changes to your model code<\/strong>. The aiDAPTIVPro toolchain covers data ingest, RAG, fine-tune, monitor, validate and inference from one interface, so a team is productive on day one rather than week three.<\/p>\n<h3>Power, thermal &amp; acoustics<\/h3>\n<p>Dual-GPU tower, air-cooled, single 230V circuit; suitable desk-side with normal office acoustics or in a small server room. <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 4 weeks.<\/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>Intel Xeon w7 \u00b7 256GB DDR5 ECC \u00b7 1TB aiDAPTIV+ cache \u00b7 4TB NVMe \u00b7 Tower<\/p>\n","protected":false},"featured_media":1995,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"QUASAR 2\u00d7 RTX PRO 4500 aiDAPTIV+ AI Workstation \u2014 34B\u201370B On-Prem | RDP GPU Mart","rank_math_description":"Dual-GPU AI workstation with 1TB aiDAPTIV+ NVMe memory extension: fine-tune and serve 34B\u201370B models on-premises. 256GB ECC, Xeon w7. Request a quote from RDP GPU Mart.","_hermes_jsonld":""},"product_brand":[],"product_cat":[21],"product_tag":[],"class_list":["post-12611","product","type-product","status-publish","has-post-thumbnail","product_cat-ai-workstations","pa_form-factor-tower","pa_gpu-model-nvidia-rtx-pro-4500-blackwell","pa_industry-bfsi-hft","pa_industry-enterprise-gccs","pa_industry-healthcare-life-sciences","pa_industry-manufacturing-industrial","pa_industry-research-higher-education","pa_series-quasar","pa_use-case-agentic-ai","pa_use-case-computer-vision","pa_use-case-fine-tuning","pa_use-case-generative-ai","pa_use-case-inference","pa_use-case-nlp-speech","pa_use-case-rag","pa_workload-fit-mid-range-aidaptiv-fine-tune","first","instock","taxable","shipping-taxable","product-type-external"],"_links":{"self":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product\/12611","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=12611"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media\/1995"}],"wp:attachment":[{"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/media?parent=12611"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_brand?post=12611"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_cat?post=12611"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/rdp.in\/gpu-mart\/wp-json\/wp\/v2\/product_tag?post=12611"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}