{"id":50,"date":"2026-06-14T16:32:42","date_gmt":"2026-06-14T16:32:42","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/rdp-edge-node-short-depth-1u\/"},"modified":"2026-07-06T01:47:58","modified_gmt":"2026-07-06T01:47:58","slug":"carina-1x-l4-edge-ai-node","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/carina-1x-l4-edge-ai-node\/","title":{"rendered":"CARINA 1\u00d7 L4 Edge AI Node"},"content":{"rendered":"<p>The CARINA 1\u00d7 L4 Edge AI Node brings AI inference to the edge \u2014 a short-depth 1u node with 1\u00d7 NVIDIA L4 (24 GB GDDR6) built to run private, low-latency AI at the site where data is created: a factory floor, retail store, hospital, branch or remote facility. Data never has to travel to the cloud; latency stays low and prompts stay in-house, in INR, on a GST invoice.<\/p>\n<p>Engineered for deployment outside a primary data centre, it fits short-depth and edge racks, runs the same software stack as RDP&#8217;s core servers, and ships with redundant power and BMC\/IPMI for lights-out remote management of a fleet of sites.<\/p>\n<h3>Key highlights<\/h3>\n<ul>\n<li><strong>1\u00d7 L4 \u00b7 24 GB GDDR6<\/strong> \u2014 efficient AI inference and light fine-tuning at the edge.<\/li>\n<li><strong>Short-depth 1U<\/strong> \u2014 fits edge, retail and branch racks where standard-depth servers won&#8217;t.<\/li>\n<li><strong>Intel Xeon 6 + 128 GB DDR5 ECC<\/strong> \u2014 local pre\/post-processing and orchestration without backhaul.<\/li>\n<li><strong>2\u00d7 10 GbE<\/strong> \u2014 high-throughput Ethernet; data stays at the site.<\/li>\n<li><strong>Redundant PSU, BMC\/IPMI<\/strong> \u2014 remote power, console and health monitoring for unattended sites.<\/li>\n<li><strong>Low-latency local inference<\/strong> \u2014 no round-trip to the cloud.<\/li>\n<li><strong>Make-in-India OEM<\/strong> \u2014 predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support for distributed estates, GeM-procurable.<\/li>\n<li><strong>Fleet upgrade path<\/strong> \u2014 standardise the edge tier and scale the core with GPU servers and micro data centers.<\/li>\n<\/ul>\n<h3>AI workload fit (what it actually runs \u2014 honestly)<\/h3>\n<ul>\n<li><strong>Edge inference (primary):<\/strong> serve quantised models and multiple small models locally for low-latency AI.<\/li>\n<li><strong>Vision &amp; multimodal:<\/strong> real-time defect detection, surveillance analytics and multimodal inference on local camera\/sensor feeds.<\/li>\n<li><strong>RAG &amp; agentic:<\/strong> private, on-site RAG and agent back-ends over local document stores.<\/li>\n<li><em>Engineering note:<\/em> the NVIDIA L4 (24 GB, low-power, single-slot) is built for inference and light fine-tuning, not large-model training \u2014 it is the right tool for low-power, low-latency edge AI. For heavy training, use a GPU Server or rack-scale system at the core.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>This sits at the <strong>deploy-at-the-edge<\/strong> stage: the node you put where data is generated to keep latency low and data resident. With 24 GB GDDR6 in a compact, remotely-managed chassis, it is sized to <strong>sustain<\/strong> real local inference where backhauling to the cloud is too slow, too costly, or not permitted.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>Manufacturing<\/strong> \u2014 real-time vision QA on the line.<\/li>\n<li><strong>Retail &amp; logistics<\/strong> \u2014 in-store \/ in-warehouse vision and forecasting.<\/li>\n<li><strong>Healthcare<\/strong> \u2014 on-site clinical inference, PHI never leaving the building.<\/li>\n<li><strong>Government &amp; defence<\/strong> \u2014 air-gapped private AI at the site.<\/li>\n<li><strong>Energy &amp; utilities<\/strong> \u2014 inference at remote or rugged facilities.<\/li>\n<li><strong>Smart cities<\/strong> \u2014 traffic, safety and sensor analytics at the edge.<\/li>\n<\/ul>\n<h3>Performance \u2014 and how to be sure<\/h3>\n<p>We don&#8217;t publish inflated peak numbers. The honest picture: 24 GB GDDR6 across 1\u00d7 L4 is sized to serve quantised models and run real-time vision at the edge. <strong>Want certainty? Request a free benchmark of your models and feeds on this exact configuration before you buy<\/strong>; we&#8217;ll send back real latency and throughput for your workload.<\/p>\n<h3>Series &amp; upgrade path<\/h3>\n<ul>\n<li><strong>CARINA<\/strong> (entry edge tier) \u2014 <em>this<\/em>.<\/li>\n<li><strong>Edge ladder:<\/strong> L4 (low-power inference) \u2192 L40S (performance inference) \u2192 RTX PRO 6000 Blackwell (high-capacity edge).<\/li>\n<li><strong>When to step up:<\/strong> centralise heavy training at the core; keep inference at the edge \u2014 talk to an architect about the hub-and-spoke topology.<\/li>\n<\/ul>\n<h3>On-prem vs cloud \u2014 the TCO case<\/h3>\n<p>At the edge, owning beats renting twice over: you remove both round-trip latency and cloud egress, and keep data resident at the site. RDP pricing is fixed in INR with a GST input-credit-eligible invoice \u2014 ask for a <strong>3-year TCO comparison<\/strong> across your sites.<\/p>\n<h3>Software &amp; day-one readiness<\/h3>\n<p>Ships <strong>pre-configured to serve<\/strong>: NVIDIA driver, CUDA, cuDNN, Docker and NVIDIA Container Toolkit, with vLLM \/ Triton \/ TensorRT-LLM and PyTorch on Ubuntu LTS. Optional fleet-management, managed inference-stack and observability for distributed estates.<\/p>\n<h3>Power, cooling &amp; rack integration<\/h3>\n<p>A Short-depth 1U node with redundant PSUs, sized for edge and retail racks \u2014 specify site power and cooling. <em>(Exact PSU rating, BTU, airflow, depth and operating-environment figures confirmed on the build sheet.)<\/em> BMC\/IPMI enables lights-out management of unattended sites.<\/p>\n<h3>Deployment, warranty &amp; support<\/h3>\n<ul>\n<li><strong>Made to order<\/strong>, built and burned-in in India; lead time confirmed at quote.<\/li>\n<li><strong>In the box:<\/strong> node, rails, power cables, quick-start, and the pre-installed AI software stack.<\/li>\n<li><strong>Onsite warranty + AMC<\/strong> with pan-India coverage for distributed sites and an RMA\/escalation path <em>(exact terms confirmed at quote)<\/em>.<\/li>\n<\/ul>\n<h3>Why RDP<\/h3>\n<p>14 years of Make-in-India infrastructure and <strong>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<h3>Buy with confidence<\/h3>\n<p>This is an edge AI node, made to order \u2014 <strong>talk to an RDP solution architect<\/strong>, design the right edge topology and 3-year TCO, and <strong>benchmark your own models on it before you commit.<\/strong> Request a quote to begin.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Intel Xeon 6 \u00b7 128 GB DDR5 ECC \u00b7 4 TB NVMe \u00b7 24 GB GDDR6 \u00b7 Short-depth 1U<\/p>\n","protected":false},"featured_media":2084,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"CARINA 1\u00d7 L4 Edge AI Node \u2014 24 GB GDDR6, Short-depth 1U | RDP GPU Mart","rank_math_description":"Short-depth 1U edge AI node \u2014 1\u00d7 L4 (24 GB GDDR6). Run private, low-latency AI at the site. Make-in-India, GST invoice, pan-India onsite. 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