AI systems that train, fine-tune & serve — without the wait.

NVIDIA-recommended AI workstations and multi-GPU servers for deep learning, machine learning, data science and GPU rendering. Rent the compute, skip the procurement cycle.

On demand

Featured AI builds, ready to rent

HP Z8 G5 AI workstations with up to dual NVIDIA RTX Pro 6000 Blackwell, and Gcompute 4U AMD EPYC servers with 4× NVIDIA H200 — the exact systems teams are renting for training right now.

HP Z8 G5 AI2× RTX Pro 60004× NVIDIA H200Gcompute AMD Server
View AI configurations
AI & HPC hardware

From a single GPU to a training cluster

Start on a desktop AI workstation and scale to multi-GPU servers as your models and datasets grow — all configured to NVIDIA's reference designs.

Desktop

AI Workstation

Single- or dual-GPU deep-learning workstations for development, prototyping and fine-tuning at the desk.

  • 1–2× NVIDIA RTX 6000 Ada / RTX 5090
  • High-core Threadripper / Xeon W CPU
  • 128–512 GB ECC memory
  • Fast NVMe scratch + dataset storage
  • CUDA, cuDNN, PyTorch & TensorFlow ready
Great for
Model devFine-tuningInference
Datacenter

AI Server

Multi-GPU servers for serious training runs, large datasets and production inference at scale.

  • 4–8× NVIDIA GPUs, NVLink options
  • AMD EPYC dual-socket compute
  • High-bandwidth memory & NVMe
  • 25/100GbE networking, IPMI management
  • Container & cluster-ready
Great for
TrainingHPCServing
NVIDIA Recommended Hardware

Reference-grade builds, ready to run

We build to NVIDIA's recommended configurations so your frameworks just work — correct driver stack, CUDA toolkit and memory bandwidth for the model you're running.

  • RTX Ada-generation & data-center GPUs
  • Pre-validated CUDA / cuDNN / framework stack
  • Benchmarked on a representative job before dispatch
See server rentals
NVIDIA-recommended
What you can run

AI & visual compute workloads

The workloads our customers run on Global Nettech AI hardware.

Deep Learning / ML

Train and fine-tune neural networks on PyTorch, TensorFlow and JAX with the GPU memory your models demand.

Recommended: RTX 6000 Ada / multi-GPU server

Data Science & Analytics

Accelerate RAPIDS, pandas and notebook workflows on large datasets without leaving your desk.

Recommended: AI Workstation

GPU Rendering

OctaneRender, Redshift, V-Ray GPU and Blender Cycles — slash render times with GPU-dense systems.

Recommended: Rendering Server

3D Design & Animation

Real-time viewports and GPU simulation for Maya, 3ds Max, Houdini and Cinema 4D.

Recommended: High-End Workstation

GIS Engineering & CAD

Large-scene GIS, point clouds and CAD/CAE acceleration with certified pro GPUs.

Recommended: Mid/High-End Workstation

Scientific Computing / HPC

CUDA-accelerated simulation and numerical workloads on multi-GPU compute servers.

Recommended: GPU Computing Server

FAQ

Frequently asked questions

Develop and fine-tune on a 1–2 GPU workstation; train larger models on a 4–8 GPU server; scale to multi-node for the biggest jobs. We size it to your model and deadline.
Around 24 GB handles most fine-tuning and vision models; 48 GB (RTX 6000 Ada) suits larger transformers; for LLM training, H200 (141 GB) or multi-GPU. Tell us your models and we'll match it.
Yes — the OS, NVIDIA drivers, CUDA/cuDNN and your framework (PyTorch, TensorFlow, JAX) are pre-installed and tested so you start on day one.
Yes — RTX Pro 6000 Blackwell and H200 NVL nodes are available via our On-Demand Configurations.
Both — burst-rent for a training run, or a monthly/annual contract for ongoing AI workloads. Scale GPUs up for training and back down for inference.

Ready to power your next project?

Get a tested, deadline-ready workstation or server — delivered, configured and supported across India.