NVIDIA DGX Station Price Update with Configuration Details

In the rapidly expanding universe of artificial intelligence and machine learning, one truth remains constant—performance matters. And when it comes to high-performance AI workstations, NVIDIA’s DGX Station has earned its reputation as the gold standard.

As of 2025, India has seen a notable rise in AI adoption across sectors—healthcare diagnostics, fintech automation, climate modeling, and generative media to name a few. According to NASSCOM, AI adoption could add over $500 billion to India’s GDP by 2026, and hardware infrastructure is a significant part of that journey.

But serious AI comes with serious compute needs. This is where the NVIDIA DGX Station steps in—a deep learning supercomputer packed in a workstation form factor. While its capabilities are awe-inspiring, many are still unsure about its price in India, real-world use, and whether there are smarter alternatives like Cyfuture Cloud’s GPU hosting or colocation-based deployment.

Let’s explore all of that in detail—from pricing and specs to performance metrics and hosting options—so you can decide if the DGX Station is the right fit for your AI ambitions.

What Is NVIDIA DGX Station?

The NVIDIA DGX Station is essentially a personal AI supercomputer. Unlike data center servers, the DGX Station doesn’t require a massive setup. It’s designed to fit in a lab, office, or even a research environment. But don’t be fooled by its workstation size—it packs the same punch as a rack of servers.

Key Highlights:

Up to 4 NVIDIA A100 Tensor Core GPUs

Up to 320 GB HBM2e GPU memory

Integrated NVLink and NVSwitch for massive bandwidth

Built-in liquid cooling (no special cooling room needed)

AI software stack pre-installed (NGC containers, libraries, drivers)

Whether you're building large language models (LLMs), training deep neural networks, or simulating complex AI environments, the DGX Station gives you plug-and-play performance at the edge of possibility.

NVIDIA DGX Station Price: What It Costs in India (2025)

Let’s cut to the chase—how much does it cost to bring this AI beast home in India?

Price Snapshot:

Note: Prices vary based on availability, warranty plans, GST, and import logistics. Quotes from official NVIDIA partners or authorized resellers (like Rashi Peripherals or Ingram Micro) usually include 1–3 year support contracts.

Considering this, most research institutions, large enterprises, and high-end AI startups use DGX Stations for critical, resource-intensive model development. Others are opting for cloud-hosted alternatives to reduce upfront capital expense.

DGX Station vs. Server vs. Cloud: What's the Difference?

You might wonder—why not just use a server or cloud platform? Let’s quickly differentiate:

While the DGX Station is perfect for deep research, it may not be cost-effective for short-term or unpredictable AI workloads. That's where providers like Cyfuture Cloud come in with GPU hosting and colocation server options tailored for different business sizes.

DGX Station: Deep Dive Into Configuration

Let’s unpack what you’re actually getting with a DGX Station A100 model.

Hardware Specifications:

GPU: 4x NVIDIA A100 40/80 GB (with NVLink)

GPU Memory: Up to 320 GB HBM2e (shared memory)

CPU: AMD EPYC 7742 (64-core)

RAM: 512 GB DDR4 ECC Memory

Storage: 1.92 TB NVMe SSD (boot) + 7.68 TB NVMe SSD (data)

Cooling: Built-in liquid cooling

Networking: 2x 10G LAN Ports

Power: Dual 1400W redundant power supplies

Software Pre-installed:

Ubuntu Linux OS

NVIDIA Deep Learning Stack (NGC, Docker, drivers, CUDA, cuDNN)

Kubernetes support and ML frameworks like TensorFlow, PyTorch

This out-of-the-box integration makes it ideal for teams that don’t want to worry about complex configurations or GPU bottlenecks.

Who Uses DGX Station in India?

Given the high price tag, the DGX Station is typically found in:

Academic institutions (IITs, IISc, BITS Pilani for AI research)

HealthTech R&D labs (genomics, disease prediction)

FinTech analytics teams (risk modeling, fraud detection)

Generative AI startups building LLMs or media applications

Government and defense AI programs

But not every organization needs to buy one. With Cyfuture Cloud's GPU-powered hosting or colocation, businesses can now run their AI models using shared or dedicated GPU resources at a fraction of the cost.

Smarter Choice: Hosting DGX-Equivalent Performance on Cloud

Instead of spending ₹90 lakhs upfront, many businesses are choosing GPU cloud hosting models that allow pay-per-use flexibility and managed environments.

How Cyfuture Cloud Supports AI Workloads:

A100 GPU Hosting Plans with hourly/monthly billing

Hybrid cloud + colocation for teams owning their own A100 servers

Tier-III certified data centers in Noida, Bengaluru, and Jaipur

Seamless vertical and horizontal GPU scaling

Expert AI ops support, custom training environment setup

Sample GPU Cloud Plan (Cyfuture Cloud):

2x A100 80 GB

64 vCPUs, 512 GB RAM

₹2.2 – ₹2.8 lakhs/month (fully managed)

With 99.99% uptime, DDoS protection, remote hands, and API-level GPU control

This not only lowers cost but also speeds up deployment, especially for startups or teams running time-bound research projects.

Conclusion

The NVIDIA DGX Station is undoubtedly a marvel of engineering and performance. It empowers researchers, developers, and enterprises to work on cutting-edge AI without the overhead of data center infrastructure. But with a price tag crossing ₹90 lakhs in India, it’s not accessible to all.

That’s where cloud-based GPU hosting and colocation services offered by platforms like Cyfuture Cloud provide a compelling middle path. Whether you want to run transformer models, fine-tune vision algorithms, or analyze massive datasets, you don’t need to buy a DGX—you just need access to its power.

In today’s AI-driven economy, it’s not about owning the most powerful hardware—it’s about accessing the right performance, at the right price, from the right place.