GPU Cloud
Dedicated, on-demand GPU instances for model training, inference, and rendering workloads — without the multi-year reserved-instance commitments larger providers require. Each GPU is exclusively yours, not shared with other tenants, so performance stays consistent.
What's included
Built to actually work the way you need it to
Dedicated, on-demand GPU instances for model training, inference, and rendering workloads — without the multi-year reserved-instance commitments larger providers require. Each GPU is exclusively yours, not shared with other tenants, so performance stays consistent.
- Dedicated GPUs — never shared with other tenants
- Pre-installed ML frameworks (PyTorch, TensorFlow)
- Per-second billing available
Performance you can count on
Modern hardware throughout
Current-generation CPUs and NVMe storage across every region, not last decade's hand-me-down hardware.
Built for demanding workloads
From analytics pipelines to media delivery, the infrastructure is sized for real production load, not just benchmarks.
Consistent performance at scale
Resources are provisioned so your performance doesn't degrade as usage grows — no noisy-neighbor slowdowns.
How it works
Choose your GPU tier
Select from single-GPU to multi-GPU configurations depending on model size and training speed needs — every GPU is dedicated, not shared.
Launch with ML tooling pre-installed
Start from an image with CUDA, PyTorch, and TensorFlow already configured, or bring your own container.
Train, infer, and shut down
Run your workload and stop billing the moment you're done — no idle GPU costs. Resize your tier later without losing data.
Included with every Hosted.one plan
Choose your plan
Full pricing details ->The best cloud platform for Indian startups. Reliable, fast and developer friendly.
Frequently asked questions
Do I ever share a GPU with another customer?
No — every GPU is dedicated exclusively to your account. You never share compute with another tenant, so performance stays consistent.
Which frameworks come pre-installed?
Images ship with CUDA, PyTorch, and TensorFlow ready to go. You can also bring your own container if you need a different stack.
Can I use multiple GPUs for one training job?
Yes — multi-GPU configurations are available for distributed training, alongside single-GPU instances for smaller workloads or experimentation.
How does per-second billing work?
You're billed only for the seconds your instance is running — stop it when a job finishes and billing stops immediately, no rounding up to the hour.
Ready to get started with GPU Cloud?
Create your account and deploy in under 60 seconds.