CARINA 1× RTX PRO 4500 Blackwell AI Workstation

Overview

The CARINA 1× RTX PRO 4500 Blackwell AI Workstation is RDP’s entry-tier, single-GPU AI machine on NVIDIA’s current Blackwell generation — one RTX PRO 4500 Blackwell with 32 GB of GDDR7 in a quiet, air-cooled desk-side tower. It gives a developer or small team a private, on-premises workstation to build, fine-tune and run modern AI models — with Blackwell’s FP4 acceleration for efficient inference, your data kept in-house, costs fixed in INR, and day-one readiness.

A workstation-class Intel Xeon W-2500 with ECC memory, 64 GB DDR5 and 2 TB NVMe keep the GPU fed for real iteration — the entry rung of the CARINA → QUASAR → DRACO ladder, on this year’s silicon rather than last year’s.

Key highlights

• Current-gen RTX PRO 4500 Blackwell (32 GB GDDR7) — Blackwell architecture with FP4 for efficient modern-model inference; ECC GPU memory.
• Workstation-class Intel Xeon W-2500 + 64 GB DDR5 ECC — error-correcting platform for stable long runs (not a consumer board).
• 2 TB NVMe — fast local datasets, checkpoints and weights; no egress fees.
• Quiet, air-cooled tower — office-friendly; no server room.
• On-prem data sovereignty — IP and data stay in-house; DPDP-friendly.
• Make-in-India OEM — INR pricing, GST invoice (HSN 8471), pan-India onsite support, GeM-procurable.
• Upgrade path — step up to the RTX PRO 5000 / 6000 Blackwell or to 2×/4× (QUASAR/DRACO).

AI workload fit

• Inference: serve quantised models up to ~30–34B (4-bit) on the 32 GB card; FP4 boosts throughput on supported runtimes.
• Fine-tuning: QLoRA / LoRA of 7B–13B models; full fine-tuning of small models.
• Build & prototype: vision, NLP, RAG pipelines on the 2 TB NVMe and agentic-app development — locally, no cloud bill.

Engineering note: a single 32 GB card keeps the setup simple — no multi-GPU partitioning. For larger models or batches, step up within the line.

AI workload positioning

This sits at the develop-and-prototype stage: a single-engineer workstation for building and fine-tuning small-to-mid models and running on-desk inference on current-generation hardware — far cheaper to own than continuous cloud rental, and private by design.

Industry use cases

• Software & AI teams — local model development, eval and agentic prototyping.
• Research & higher-ed — a personal AI workstation for NLP, vision and speech.
• Startups — a private fine-tuning box that avoids per-hour cloud costs.
• Manufacturing / healthcare / BFSI — on-prem development of vision, imaging and document-AI where data must stay in-house.

Performance — and how to be sure

No inflated peak numbers: a single 32 GB RTX PRO 4500 Blackwell is sized for QLoRA of 7B–13B and inference of quantised models up to ~30–34B. Request a free benchmark of your model on this exact configuration before you buy.

Series & upgrade path

• CARINA (entry, 1× — this) · QUASAR (2×) · DRACO (4×).
• Within CARINA: RTX PRO 5000 (48 GB) or 6000 (96 GB) Blackwell for more memory.
• When to step up: models >32 GB or multi-model serving → QUASAR/DRACO — talk to an architect.

On-prem vs cloud — the TCO case

For day-in, day-out development, owning beats renting: a cloud GPU running continuously adds up within months, and on-prem removes egress fees while keeping data 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-loaded: NVIDIA driver, CUDA, cuDNN, Docker and the NVIDIA Container Toolkit, with PyTorch / TensorFlow on Ubuntu LTS. Optional managed AI-stack setup available.

Power, thermal & acoustics

A single ~200 W GPU plus the Xeon W runs comfortably on a standard office circuit, air-cooled and quiet at the desk. (Exact PSU rating, BTU and dB(A) confirmed on the build sheet.)

Deployment, warranty & support

• Made to order, built and burned-in in India; lead time confirmed at quote.
• In the box: workstation, power cable, quick-start, and the pre-installed AI software stack.
• Onsite warranty + AMC, pan-India, with 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

Talk to an RDP solution architect, get a configuration and TCO tailored to your workload, and benchmark your own model on it before you commit. Request a quote to begin.

Specifications