GPU cloud servers for AI, ML and rendering — in India, in INR.
NVIDIA V100 GPU servers with PyTorch, CUDA, TensorFlow and Jupyter pre-installed. Hourly or monthly billing, snapshot backups, root access and a 99.95% SLA — affordable GPU cloud you can actually use without becoming an MLOps engineer.
Key Advantages & Architectural Highlights
Just deploy & train
PyTorch, CUDA, TensorFlow, JAX and Jupyter are pre-installed and version-pinned. SSH in and start training — no driver hell.
Hourly OR monthly billing
Pay hourly while iterating, or monthly for steady workloads. Stop the instance when you’re done and stop paying.
NVMe + snapshots
NVMe-backed datasets load fast. Snapshot the entire instance to preserve experiments or roll back a bad change.
Full root access
Install any framework, custom CUDA build or Docker image. It’s your machine — we just keep the GPUs healthy.
Production-grade SLA
99.95% SLA, isolated tenancy, ECC memory on host — built for serious workloads, not bargain-bin scraps.
India PoPs
Datasets and inference closer to your users and team — lower latency than US/EU GPU clouds.
Target Use Cases & Workloads
LLM fine-tuning
LoRA / QLoRA fine-tunes on 7B–13B open models. Bigger setups available on multi-GPU nodes.
Image gen & diffusion
Stable Diffusion XL, ControlNet, Flux — train, serve or batch-generate at production scale.
Speech & audio AI
Whisper-style speech-to-text, TTS training, audio diarisation — V100 handles it.
3D / rendering / VFX
Blender Cycles, OctaneRender and other CUDA-accelerated render pipelines.
Frequently Asked Questions
Clear, transparent answers about our enterprise cloud platform, SLAs, billing, and migrations.
Which GPUs are available? ▾
NVIDIA V100 (16 GB / 32 GB), single and multi-GPU configurations. Larger H100 / A100 nodes on request — talk to us on WhatsApp.
What’s pre-installed? ▾
Ubuntu 22.04, NVIDIA driver, CUDA, cuDNN, PyTorch (latest stable), TensorFlow, JAX, JupyterLab and conda. Docker with the NVIDIA runtime is ready too.
Can I bring my own Docker image? ▾
Yes — full root, full Docker, full NVIDIA container toolkit. Pull any image from Docker Hub, NGC or your own registry.
How fast is provisioning? ▾
Most GPU plans are live within 2–5 minutes of payment. Multi-GPU configs may take a little longer for hardware allocation.
Is there a free trial? ▾
No free trial, but hourly billing lets you spin up a V100, run for an hour or two, and stop — total spend is just a few dollars to validate fit.
Deploy in India with Low Latency & High Uptime
Tier-III Noida and Chennai datacenters, flat INR pricing with GST invoices, and 24/7 technical assistance.