DRACO 8× B200 SXM GPU Server

Overview

The DRACO 8× B200 SXM GPU Server is an Rack 8U HGX B200 rack server — the densest single-node Blackwell platform RDP builds. Eight NVIDIA B200 SXM (HGX B200) GPUs on one HGX baseboard deliver 1,440 GB HBM3e of HBM3e, linked by NVLink and NVSwitch into a single tightly-coupled accelerator with Blackwell FP4/FP8 throughput — sized to train and serve trillion-parameter-class models on one node, behind your firewall, in INR, on a GST invoice.

Engineered for organisations standing up serious AI capability on-premises, it pairs the eight GPUs with a 2× Intel Xeon 6 host, 3 TB DDR5 ECC and 60 TB NVMe, with 8× 400G InfiniBand for scale-out, redundant power and liquid cooling — and full BMC/IPMI for lights-out operation.

Key highlights

• 1,440 GB HBM3e of HBM3e across 8× B200 SXM — a single-node memory pool sized for trillion-parameter-class training and serving.
• NVLink + NVSwitch fabric — full all-to-all GPU bandwidth across all eight Blackwell GPUs for efficient tensor parallelism.
• Blackwell FP4/FP8 — next-generation throughput for training and high-efficiency inference at scale.
• 2× Intel Xeon 6 + 3 TB DDR5 ECC — high core count and memory bandwidth to feed eight Blackwell GPUs.
• Rack 8U, liquid-cooled, redundant PSU, BMC/IPMI — sustained clocks under full load, lights-out management.
• 60 TB NVMe + 8× InfiniBand NDR 400G — large local storage and a high-bandwidth scale-out fabric; no egress fees.
• On-prem data sovereignty — training data and weights stay in-house; DPDP-friendly, air-gappable.
• Make-in-India OEM — predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable.

AI workload fit (what it actually runs — honestly)

• Training & fine-tuning: full pre-training and fine-tuning of very large (toward trillion-parameter) models, tensor- and pipeline-parallel across the eight NVSwitch-linked Blackwell GPUs.
• Inference: high-efficiency FP4/FP8 serving of the largest models, or many large models concurrently.
• RAG, vision, multimodal & agentic: production pipelines on the 60 TB NVMe and large multi-agent back-ends.
• Engineering note: all eight SXM GPUs share an NVLink+NVSwitch fabric for full all-to-all bandwidth — the configuration large-model training actually needs; for scale beyond one node, multiple units link over the 400G InfiniBand fabric.

AI workload positioning

This sits at the top of single-node train-and-serve capability. With 1,440 GB HBM3e of HBM3e on an NVLink+NVSwitch fabric and 8× 400G InfiniBand, it is sized to sustain frontier-class training and high-efficiency inference on-prem — the owned alternative to renting a Blackwell cloud node continuously.

Industry use cases

• BFSI — train and serve the largest private models under data-residency rules.
• Healthcare & life sciences — on-prem training of large medical and imaging models, PHI in-house.
• Government & PSU — sovereign frontier-class AI on GeM-procurable infrastructure.
• Neocloud / AI providers — the flagship single-node Blackwell building block for a GPU cloud.
• Telecom & large enterprise — serious in-house AI capability near operations.
• Research & national labs — an institutional frontier-class training node.

Performance — and how to be sure

We don’t publish inflated peak numbers. The honest picture: 1,440 GB HBM3e of HBM3e across eight NVSwitch-linked Blackwell GPUs is sized for trillion-parameter-class training and high-efficiency serving on-prem. Want certainty? Request a free benchmark of your model and dataset on this exact configuration before you buy — we’ll send back real tokens/sec and training/fine-tune timings for your workload.

Series & upgrade path

• DRACO (flagship training tier) — this, the densest single-node Blackwell B200 platform.
• Step up in generation: the 8× B300 (Blackwell Ultra) HGX node offers still more HBM per GPU for the very largest models.
• Step up in scale: for multi-rack systems, move to RDP Rack-Scale AI Systems and AI SuperClusters — talk to an architect about the fabric.

On-prem vs cloud — the TCO case

For sustained frontier-class training, owning beats renting decisively: an always-on 8-GPU Blackwell cloud node is among the largest line items in any AI budget, 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 — ask for a 3-year TCO comparison.

Software & day-one readiness

Ships pre-configured to train and serve: NVIDIA driver, CUDA, cuDNN, NCCL, the InfiniBand stack, Docker and NVIDIA Container Toolkit, with PyTorch, vLLM / Triton / TensorRT-LLM on Ubuntu LTS. Optional Slurm/Kubernetes, managed AI-stack and observability setup available.

Power, cooling & rack integration

An Rack 8U liquid-cooled node with high power draw — plan CDU/manifold and facility water, dedicated power and InfiniBand cabling. (Exact PSU rating, BTU, flow, fabric cabling and rack-depth figures confirmed on the build sheet.) BMC/IPMI provides remote power, console and health monitoring.

Deployment, warranty & support

• Made to order, built, racked-and-stacked, cabled and burned-in in India; realistic lead time confirmed at quote.
• In the box: server, rails, power cables, quick-start, and the pre-installed AI software stack; fabric switches and cabling scoped at quote.
• Onsite warranty + AMC with pan-India coverage and an RMA/escalation path (exact term & response window confirmed at quote).

Why RDP

14 years of Make-in-India infrastructure and 300,000+ devices shipped. Indian OEM, INR pricing, GST tax invoice (HSN 8471), pan-India onsite engineers, GeM availability, and DPDP / sovereign-AI-ready deployment.

Buy with confidence

This is a flagship single-node Blackwell training server, made to order — talk to an RDP solution architect, get a configuration and 3-year TCO tailored to your workload, and benchmark your own model on it before you commit. Request a quote to begin.

Specifications