Dedicated NVIDIA GPU Servers in India
GPU Server Hosting for AI, ML & Rendering
Deploy dedicated NVIDIA GPU servers hosted inside NCXHost’s Indian data center. Built for AI training, LLM inference, machine learning, 3D rendering, CUDA workloads, video processing, and high-performance compute.
Fully-managed, Self-managed GPU servers
Choose dedicated GPU compute without cloud billing surprises.
Pick a ready GPU plan or request a custom server with your preferred GPU, CPU, RAM, NVMe storage, operating system, and management level.
Prices are exclusive of applicable taxes.
A fair price without renewal gimmicks
NCXHOST offers a simple, predictable hosting pricing structure without any hidden or unexpected fees when renewing hosting plans.
Instant Deployment, Easy Scalability
High-Performance GPU Servers for Every Workload
Train your AI models, host gaming servers, power AI-driven apps, run deep learning, 3D rendering, and data-intensive simulations all on NCXHost’s high-performance GPU servers. Get access to NVIDIA RTX 4090, A5000, A6000, H100, and more, backed by ultra-fast NVMe Gen5 SSDs for seamless performance. Whether you’re an AI researcher, game developer, or cloud computing enthusiast, experience top-tier GPU power at up to 50% lower cost than AWS & Google Cloud, with instant deployment and 24/7 expert support.
Machine Learning
Train models faster and more efficiently with GPU acceleration, accelerating your machine learning workflows.
Rendering
Achieve stunning visualizations with accelerated rendering, ideal for industries such as animation, architecture, and design.
Scientific Computing
Accelerate scientific simulations and computations, empowering researchers and scientists with faster results.
Use Cases
Built for serious GPU workloads
NCXHost GPU servers are designed for teams and businesses that need reliable, long-running compute performance instead of temporary cloud experiments.
AI Training
Train machine learning models, computer vision systems, deep learning workloads, and private AI pipelines.
LLM Inference
Run AI chatbots, private LLMs, embeddings, RAG systems, and inference APIs on dedicated hardware.
3D Rendering
Accelerate Blender, V-Ray, Unreal Engine, animation rendering, and GPU-based production pipelines.
Scientific Compute
Run simulations, research workloads, CUDA applications, and parallel compute tasks with full server control.
Video Processing
Use GPU acceleration for encoding, transcoding, upscaling, AI video workflows, and media automation.
Why NCXHost
AI-ready hardware hosted inside our Indian data center.
Get dedicated GPU compute with predictable monthly pricing, direct infrastructure support, and the flexibility to run your own stack.
- Dedicated NVIDIA GPU server, not shared GPU credits.
- Suitable for long-running AI, rendering, and compute workloads.
- Linux or Windows installation based on your requirement.
- Custom CPU, RAM, NVMe, and storage options available.
- Managed setup and monitoring available for business users.
Dedicated Performance
Your workload runs on dedicated GPU hardware with better control and predictable performance for production use.
Dedicated Performance
Your workload runs on dedicated GPU hardware with better control and predictable performance for production use.
Full Server Control
Install CUDA, Docker, PyTorch, TensorFlow, custom drivers, rendering tools, or your preferred stack.
Local Support
Get direct support from NCXHost for setup, troubleshooting, networking, monitoring, and custom requirements.
Dedicated GPU vs Cloud GPU
Better for long-term, production GPU workloads.
Cloud GPU is useful for short experiments. Dedicated GPU servers are stronger when your workload runs continuously.
+9170990 64541
24/7 expert support
Get instant access to our dedicated support team, available 24/7 to help you resolve any issues or answer your questions.
FAQ
Our GPU servers are ideal for AI/ML model training and inference, Stable Diffusion, video rendering, scientific computing, data analytics, and any workload that benefits from massive parallel processing.
We currently provide NVIDIA RTX-series GPUs such as the RTX 3090, with 24 GB of VRAM. Additional models may be added based on demand and availability.
Yes. Our GPU servers support modern CUDA toolkits and are fully compatible with frameworks like PyTorch and TensorFlow. You can install them directly or request a preconfigured environment.
Our GPU hosting plans provide dedicated access to the GPU hardware in your plan. This ensures consistent performance and predictable runtimes for your workloads.
Yes. You can run multiple Docker containers or processes on the same GPU server, as long as you manage VRAM and compute usage appropriately.
Yes. You can start with a single GPU and move to higher-end or multiple GPUs later. Our team can help you choose the right configuration when you’re ready to scale.
Absolutely. Many startups use our GPU servers as a cost-effective alternative to expensive public clouds. You pay a predictable monthly price without surprise overage bills.
GPU servers run in our secure data center environment with network firewalls, access controls, and isolation between customers. You can further harden security with your own OS-level firewall, SSH key access, and encryption.
