QUASAR 2× RTX PRO 4500 aiDAPTIV+ Workstation

Overview

Two GPUs, 70B-class models, and none of it leaves your building. Dual NVIDIA RTX PRO 4500 Blackwell cards with a 1 TB aiDAPTIV+ NVMe cache take a team from experimenting on 13B models to fine-tuning the 34B–70B class that most production Indian enterprise workloads actually settle on.

Key highlights

• 2× NVIDIA RTX PRO 4500 Blackwell 32GB — 64 GB aggregate VRAM for model-parallel work.
• 1 TB aiDAPTIV+ cache (U.2 + M.2 enterprise NVMe) — the difference between “won’t load” and “runs”.
• 34B–70B fine-tuning with LoRA/QLoRA, plus BF16/INT4 inference.
• 256 GB DDR5 ECC RDIMM on an Intel Xeon w7 platform — real data-prep headroom.
• 4 TB NVMe for datasets, checkpoints and multiple model versions.
• Desk-side or small server-room footprint — no rack or facility cooling required.
• DPDP and data-residency preserved by design: the data never crosses your boundary.

AI workload fit

• Fine-tuning 34B–70B models (LoRA/QLoRA) on proprietary corpora.
• Production inference for a department or business unit.
• RAG over large private document estates.
• Agentic AI workflows with tool use and multi-step reasoning.
• Generative AI, computer vision and NLP & speech workloads.
• Not for foundation-model pretraining — step up to an RDP GPU server.

AI workload positioning

The workhorse rung. Most organisations discover their real requirement is a well-tuned 34B–70B model on their own data rather than a frontier model on someone else’s cloud — 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 capacity technology, not a bandwidth one — 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.

Industry use cases

• BFSI: risk, fraud and document-intelligence models tuned on in-house data.
• Healthcare & life sciences: clinical language models under residency obligations.
• Manufacturing: vision QC and predictive-maintenance models trained on plant data.
• Enterprise & GCCs: a shared team box for AI platform and applied-AI groups.
• Research & education: lab-scale fine-tuning without competing for cluster time.

Performance & how to be sure

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 — 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 “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

QUASAR is the performance tier. Below it sits the CARINA 1× RTX PRO 5000 (13B–34B); above it the QUASAR 2× RTX PRO 5000 (70B) and the DRACO workstations (90B–180B), then RDP GPU servers for 180B+ and true multi-GPU training. Identical software stack throughout.

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, and the aiDAPTIV+ memory-management layer, which is PyTorch-compliant and needs no changes to your model code. 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.

Power, thermal & acoustics

Dual-GPU tower, air-cooled, single 230V circuit; suitable desk-side with normal office acoustics or in a small server room. 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 4 weeks.

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