⚙ GPU Dedicated Servers

GPU Dedicated Servers in India for AI, Deep Learning & Rendering

When CPUs hit their limit, bare-metal NVIDIA GPU servers keep your training, inference and rendering jobs moving.

Dedicated NVIDIA H100 and A100 GPUs with full root access, ECC memory and NVMe storage. No virtualization, no shared resources. Plans from ₹5,999/month.

Key Features of ICSDC GPU Dedicated Servers

Every ICSDC GPU dedicated server gives you exclusive NVIDIA GPU resources, high-bandwidth memory and full root access, so your workloads run consistently.

Dedicated GPU Compute Power

Get exclusive access to full GPU resources, with no sharing and no noisy neighbours, for consistent performance on every job.

High Memory & Fast Data Throughput

HBM3 and HBM2e memory plus NVMe storage move large datasets and parallel tasks without bottlenecks.

Optimized for AI, ML & Rendering

Train models, run inference and simulations, and render video or 3D scenes on hardware made for compute-intensive work.

Full Control & Custom Environments

Install your own OS, NVIDIA drivers, CUDA and frameworks like TensorFlow or PyTorch, and tune the setup to your workload.

Choose the Right GPU Server Plan

Simple pricing based on GPU type, resources, and performance level - no hidden complexity.

Entry GPU

₹5,999 //mo

Single GPU for inference, development, and smaller workloads

1x NVIDIA A100
40 GB HBM2e Memory
16 Core CPU
64 GB ECC RAM
960 GB NVMe SSD
10 TB Bandwidth

Get Started

The Technology Behind High-Intensity Workloads

Every ICSDC GPU dedicated server runs on physical NVIDIA hardware, built for sustained AI, ML, rendering and HPC workloads.

True Bare-Metal GPU Performance

Your GPU dedicated server runs directly on physical hardware with no virtualization layer, so your workloads get full, uninterrupted access to GPU resources without sharing them with other tenants.

Enterprise-Class NVIDIA GPU Options

Choose NVIDIA H100, A100 or L40S GPUs for AI training, machine learning, rendering and HPC, with support for CUDA-based frameworks.

Full Root-Level Server Control

Get complete root access to choose your operating system, install NVIDIA drivers, manage GPU settings and tune performance for your exact workload.

High-Speed Network Connectivity

High-bandwidth uplinks support low-latency data transfer, remote access and distributed processing, with 10 TB to unlimited bandwidth depending on the plan.

Multi-GPU Configurations Available

Scale compute power with multi-GPU servers, such as 4x NVIDIA A100, for parallel processing, large-model training, rendering pipelines and simulations.

Global Deployment Options

Deploy GPU servers in strategically located data centers to reduce latency, meet compliance needs, and support geographically distributed teams or applications.

ECC Memory for Compute Stability

Enterprise-grade ECC RAM detects and corrects memory errors, protecting data integrity during long-running training, rendering and simulation jobs.

Optimized Thermal & Power Design

Cooling and power management are configured to hold consistent GPU performance during sustained, high-load operation.

GPU Compatibility With Containers & Virtualization

Run container platforms and virtualization tools with GPU passthrough while keeping direct access to the hardware.

Ready-to-Use GPU Software Stack

Start faster with optional pre-installed NVIDIA drivers and CUDA libraries for TensorFlow, PyTorch and other GPU-accelerated frameworks.

Flexible Billing & Configuration Options

Pick the GPU, memory and storage configuration that fits your workload, billed monthly in INR.

Secure & Isolated Infrastructure

Hosted in secure data centers with network protection and controlled access, plus private networking options to keep your GPU workloads isolated.

Best Uses for a GPU Dedicated Server: AI, Rendering, HPC & More

From LLM training to medical imaging, a GPU dedicated server gives parallel workloads the consistent performance they need.

AI & Language Models

Train, fine-tune and run large language models and NLP workloads on a GPU dedicated server. GPU acceleration speeds up training, embeddings and inference for chatbots, translation tools, content moderation and text analytics.

3D Rendering & Visual Workloads

Cut render times for complex scenes with GPU-accelerated rendering engines. Dedicated GPU memory handles high-resolution textures, lighting calculations and real-time previews for design studios, architects and animation teams.

Autonomous Systems & Simulation

Process large simulation and sensor datasets and train decision-making models on GPU-powered servers. Multi-GPU configurations run parallel workloads for research, testing and robotics development.

Blockchain & Distributed Compute

Run GPU-intensive blockchain tasks such as cryptographic processing, smart contract execution and transaction validation. Dedicated GPU resources keep performance predictable for compute-driven, decentralized environments.

AI Inference & Model Serving

Deploy trained models for real-time inference in production. A dedicated GPU gives consistent performance for image recognition, speech processing, recommendation systems and other inference-heavy applications.

Medical Imaging & Data Analysis

Process large imaging datasets such as CT and MRI scans with GPU-accelerated models. High-memory GPUs and stable performance support healthcare analytics, research and diagnostic tooling.

Virtual Reality & Simulation Environments

Power immersive VR applications with low latency and high frame rates. Dedicated GPUs handle real-time rendering, physics calculations and interactive simulations for training, education and enterprise use.

Game Development & Build Pipelines

Speed up game engine workflows with GPU-accelerated builds, asset processing and real-time testing. Suited to studios building high-quality visuals, physics simulations and performance-critical game components.

Financial Analytics & Fraud Detection

Run GPU-accelerated models that analyse large transaction datasets in near real time. Parallel processing helps detect anomalies and patterns for fraud detection, risk analysis and financial modelling.

Ready to see if a GPU Dedicated Server fits your workload?

Talk to our GPU infrastructure experts and find the right configuration for your AI, rendering, or HPC needs.

Compare GPU Capabilities Across Workloads

GPU Model	Memory / Type	Bandwidth (GB/s)	Power (W)	FP64 (TFLOPS)	FP32 (TFLOPS)	INT8 (TOPS)	Suggested Use Cases
NVIDIA L40S	48 GB GDDR6	~864	~350	N/A	~91.6	733	Inference, graphics, mixed AI/visual workloads
NVIDIA H100	80 GB HBM3	~3350	~700	N/A	~60	1216	Large AI training, HPC & deep learning
NVIDIA Tesla T4	16 GB GDDR6	~300	~70	N/A	~8.1	130	Edge inference, video transcoding
NVIDIA L4	24 GB GDDR6	~300	~72	N/A	~30	147	AI inference, video/vision workloads
NVIDIA H200	141 GB HBM3e	~4800	~700	N/A	N/A	N/A	Next-generation AI training & HPC
NVIDIA A30	24 GB HBM2	~933	~165	N/A	~10.3	330	AI training, general HPC tasks
AMD MI210	64 GB HBM2e	~1600	~300	~11.9	~22.7	N/A	FP64-heavy HPC, large compute jobs
NVIDIA A100	40 GB HBM2e	~1555	~250-300	~9.7	~19.5	624	AI training, analytics
NVIDIA RTX A4000	16 GB GDDR6 ECC	~448	~140	N/A	~19.2	N/A	Graphics & mid-range compute
NVIDIA RTX A5000	24 GB GDDR6 ECC	~768	~230	N/A	~27.8	~444	High-end graphics, AI & compute

Why Choose ICSDC for Your GPU Dedicated Server in India?

An ICSDC GPU dedicated server is built for organisations that need dependable performance, consistent availability and hardware that holds up under sustained, compute-heavy workloads.

Reliable 99.9% Uptime Commitment

Your GPU server is hosted on infrastructure designed for high availability, with redundant power, network connectivity and continuous monitoring to keep your workloads online.

Built for Long-Running, High-Load Tasks

Run AI training, data processing, rendering and simulation jobs for hours or days while keeping performance stable under sustained load.

Enterprise-Grade Data Center Environment

Secure, professionally managed data centers with controlled access, power backup and network redundancy support business-critical workloads.

Balanced Compute, Memory & Storage

Each configuration pairs the GPU with matching CPU cores, RAM and NVMe storage, so no single component becomes the bottleneck.

Dedicated Resources, Predictable Performance

Your GPU, memory and compute are not shared with other users, so performance stays predictable and your workloads stay isolated.

One Server for Many GPU Workloads

Use the same GPU dedicated server for AI and machine learning, rendering, analytics and simulation, with no need to change infrastructure.

Better Value for Parallel Workloads

For workloads that benefit from parallel processing, a GPU dedicated server is more efficient than a CPU-only system, with predictable monthly pricing in INR.

Scale as Your Workloads Grow

Move to a larger or multi-GPU configuration as requirements grow, without rebuilding your environment from scratch.

NVIDIA GPU Options for ICSDC GPU Dedicated Server Plans

From LLM training to virtual desktops (VDI), choose the NVIDIA GPU that matches your workload.

NVIDIA GH200 Grace Hopper Superchip

Combines an NVIDIA Grace CPU and a Hopper GPU in one superchip, linked by a high-bandwidth, coherent connection. Built for large-scale AI training and HPC workloads that need low-latency data movement.

NVIDIA HGX H100 Tensor Core GPU

Hopper-based GPU with fourth-generation Tensor Cores and a Transformer Engine, optimized for large language models and deep learning training. Suited to high-throughput parallel compute at scale.

NVIDIA A100 Tensor Core GPU

Ampere-based, multi-purpose GPU for AI training, inference and analytics. Multi-Instance GPU (MIG) support lets you split one GPU into isolated instances for workload isolation and resource partitioning.

NVIDIA L40S GPU

Ada Lovelace data-center GPU that combines AI inference with graphics acceleration. Suited to mixed workloads, including rendering, generative AI and visual compute.

NVIDIA A40 GPU

Ampere-based professional GPU with 48 GB of memory, focused on visual computing, ray tracing and simulation. Supports graphics-heavy and AI-assisted workflows.

NVIDIA A16 GPU

Designed for high-density virtual desktop infrastructure (VDI), with multiple GPUs per board for efficient GPU sharing. Delivers a consistent experience across many concurrent desktops.

When Should You Choose a GPU Dedicated Server?

Training or fine-tuning AI and machine learning models that need parallel processing
Large datasets that need more compute and memory bandwidth than a CPU server can deliver
Applications held back by CPU-only performance
Rendering, simulation or other visual compute tasks
Workloads that need an isolated, dedicated GPU with no sharing
Low-latency inference and high-throughput compute in production
Full control over GPU drivers, CUDA, frameworks and the operating system
Short-term or bursty workloads? GPU cloud hosting may be a better fit.

Read ICSDC GPU Dedicated Server Client Stories

Arjun Mehta

Machine Learning Engineer, AI Research Firm

We moved to a GPU dedicated server when training times on CPUs started affecting our research timelines. With dedicated GPU resources, training large models became far more predictable.

Sneha Kulkarni

Lead Developer, Data Analytics Company

Our team works with large datasets and runs multiple experiments daily. ICSDC GPU servers helped us reduce processing delays, especially during model testing and validation. The consistent performance has made it easier to plan workloads without worrying about sudden slowdowns.

Rohit Khanna

Technical Director, Media Production Studio

We handle heavy rendering workloads for video and 3D projects. Earlier, render times were hard to estimate. With a GPU dedicated server, jobs run faster and more consistently, which has improved our delivery schedules and reduced idle time for the team.

Ankit Verma

Backend Engineer, SaaS Platform

Our use case is mainly inference and batch processing rather than training. The dedicated GPU setup has been reliable for production workloads, and isolation from shared environments helped us avoid performance variability during peak usage hours.

Neha Iyer

Research Associate, Healthcare Technology Organisation

We work with medical imaging data that requires long-running compute tasks. GPU acceleration significantly reduced processing time while maintaining accuracy. The server stability has been important for us, especially during continuous analysis runs.

FAQs about ICSDC GPU Dedicated Server

01What is a GPU Dedicated Server used for?

A GPU Dedicated Server is used for workloads that benefit from parallel processing, such as AI training, machine learning, rendering, simulations, and large-scale data processing.

02How is a GPU Dedicated Server different from a CPU server?

GPU servers are designed to handle many computations simultaneously, while CPU servers handle tasks sequentially. This makes GPUs much faster for AI, graphics, and compute-heavy workloads.

03Do I get full control over the GPU server?

Yes. You get full root access, allowing you to install your preferred operating system, GPU drivers, libraries, and frameworks based on your workload requirements.

04Can I use the GPU server for both training and inference?

Yes. GPU Dedicated Servers can be used for model training, fine-tuning, inference, rendering, and other GPU-accelerated tasks depending on the configuration you choose.

05Are GPU resources shared with other users?

No. The GPU, CPU, memory, and storage resources are fully dedicated to your server, ensuring consistent and predictable performance.

06What kind of workloads benefit most from GPU servers?

Workloads involving large datasets, image or video processing, deep learning models, scientific simulations, and real-time rendering benefit the most from GPU acceleration.

07Can I scale or upgrade my GPU server later?

Yes. Depending on availability, configurations can be adjusted to support higher GPU capacity, additional resources, or different GPU models as your requirements evolve.

08Is technical expertise required to manage a GPU Dedicated Server?

Basic server management knowledge is recommended. However, ICSDC provides support to help with setup guidance, access issues, and general configuration questions.

Get Your GPU Dedicated Server in India Today

Bare-metal NVIDIA GPU dedicated servers from ₹5,999/month. Full root access, ECC memory, no virtualization.