DRACO 8× B300 SXM aiDAPTIV+ AI Server

Overview

Blackwell Ultra — the largest single node RDP builds. Eight NVIDIA B300 SXM GPUs in one NVSwitch domain with a 16 TB aiDAPTIV+ cache, reaching the 671B class. For organisations whose model ambitions have outgrown every other rung but who still require the system to sit inside their own perimeter.

Key highlights

• 8× NVIDIA B300 (Blackwell Ultra) SXM — the highest-memory Blackwell node available.
• NVSwitch all-to-all single memory domain for frontier-scale distributed training.
• 16 TB aiDAPTIV+ cache for resident multi-model estates and very long context.
• Native FP4/FP8 — matched to how frontier models actually ship today.
• 2 TB DDR5 ECC host, 8× 400G OSFP fabric, full BMC/Redfish management.
• Clusters over InfiniBand or Spectrum-X Ethernet into multi-node training capacity.
• The on-premises answer to renting frontier capacity — sovereign and air-gap capable.

AI workload fit

• Frontier-adjacent LLM training at 671B class.
• Full-parameter fine-tuning of very large models.
• Highest-throughput production inference at FP4/FP8.
• HPC & AI convergence for scientific and industrial simulation.
• Sovereign AI national programmes and strategic research.
• The building block of a multi-node AI factory.

AI workload positioning

The top of the single-node ladder. Beyond this point the conversation moves from servers to rack-scale systems — GB300 NVL72 and multi-rack superclusters — where the unit of purchase is a rack, not a chassis. We will tell you plainly when that threshold has been crossed rather than sell another node. aiDAPTIV+ extends usable model memory onto high-endurance enterprise NVMe. At this tier it is not a substitute for HBM — it is what keeps additional large models and long-context state resident without adding nodes. It remains a capacity technology; sustained throughput is confirmed in a scoped proof-of-concept.

Industry use cases

• Public sector & sovereign: strategic national AI capability on domestic infrastructure.
• Neocloud: premium multi-tenant capacity at the top of the price ladder.
• Research & education: national-lab-class research compute.
• Defence & aerospace: classified frontier work behind an air gap.
• BFSI & HFT: the largest proprietary models with absolute data control.

Performance & how to be sure

B300 Blackwell Ultra leads on memory capacity and low-precision throughput; as always the published peaks are NVIDIA’s ideal-condition figures, and real throughput depends on parallelism strategy, precision and interconnect topology. Rather than quote a tokens/sec figure that will not match your workload, RDP offers a “benchmark your model” 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.

Series & upgrade path

Below: 8× B200 SXM (405B) and 4× H200 SXM. Above: rack-scale GB300 NVL72, the GB300 NVL72 Supercluster (8-rack containerised), and AMD rack-scale alternatives. Beyond a single node, RDP quotes racks rather than chassis.

On-prem vs cloud (TCO)

For sustained daily AI work this configuration removes per-GPU-hour billing, queueing for scarce instances, and egress charges on your own data — 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.

Software & day-one readiness

Ships workload-ready: Ubuntu LTS or RHEL, NVIDIA driver + CUDA + cuDNN, container runtime, Kubernetes/Slurm integration, and the aiDAPTIV+ memory-management layer — PyTorch-compliant, no model-code changes. Standard serving stacks (vLLM, SGLang, TensorRT-LLM, NVIDIA Dynamo) supported.

Power, thermal & acoustics

8U Blackwell Ultra chassis at the highest power density in the single-node range — liquid cooling is effectively mandatory. Facility power, cooling and floor-loading survey is included in the quotation process. Exact wattage, BTU and dB(A) figures come from RDP bench measurement rather than estimates — ask for the site-readiness sheet with your quote.

Deployment, warranty & support

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 — typically 12–16 weeks, subject to GPU allocation.

Why RDP

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 — with predictable INR pricing, GST invoicing and pan-India onsite service.

Buy with confidence

Use Request a Quote to reach an RDP solution architect for sizing, a benchmark-your-model session, financing options and a delivery plan. No obligation.

Specifications