GPU Cloud India

Cloud GPU Pricing India

Transparent GPU pricing in INR. Compare all available GPUs side by side.

fromH100217.89·A100104.49·A600063.99/hr
Trusted by 27,343 AI developers
Trusted worldwide

Powering teams that push boundaries

27,000+AI developers
50M+GPU hours served
99.9%Uptime SLA
<90sInstance launch

Trusted by companies including: Tesla, Hugging Face, Kaggle, Zoho, Weights & Biases, upGrad, Saama

How it works

Launch AI Workspaces
in Minutes

From template to production in five steps. No hardware hassles—just pure computational power on-demand.

01

Choose Template

Pick a pre-configured framework and pair it with the right GPU for your ML workload.

PyTorchTensorFlowComfyUIAutomatic1111
02

Configure Resources

Select GPU type, count, and storage. Scale from a single GPU to a multi-GPU cluster.

H100A6000A100RTX 6000 Ada20GB–2TB
03

Launch Instance

One click and your fully configured environment is ready in under 90 seconds.

One-click launchPreconfigured environment
04

Development Tools

Multiple access methods to work your way. Install anything you need.

JupyterLabVS Code WebSSH AccessConnect via your IDE
05

Deploy Apps

Ship APIs, web apps, and ML models to production.

GradioStreamlitFastAPICustom Endpoints

Ready to get started?

View GPU Pricing
CLI & SDK

Your GPU,
Your Terminal

Manage your entire GPU lifecycle from the command line or Python code.

Instance Management

Create, pause, resume, and destroy GPUs from the CLI or Python.

jl create --gpu A100

Managed Runs

Upload code, install deps, run scripts, stream logs — one command.

jl run train.py --gpu A100

File Transfer & SSH

Copy files and SSH into instances without leaving your terminal.

jl ssh <id>

Agent-Native

Let Claude Code, Cursor, or Codex drive GPU experiments.

jl setup
~/project
$ pip install jarvislabs
$ jl create --gpu A100
✓ Instance ready in 38s
$ jl run train.py --gpu A100
⠋ Uploading code & starting training...
bash$ pip install jarvislabs
Testimonials

Loved by AI Practitioners

Thousands of researchers, engineers, and teams trust JarvisLabs for their GPU workloads.

Pricing

Pay as you go

All prices shown in INR for reference. Choose from the latest NVIDIA GPUs at competitive hourly rates, with no minimum commitments. Paused instances only incur storage fees.

GPU rental starts from ₹36/hr

GPU Rental Pricing (INR)

GPUs
Nvidia logoH200 SXM
271.35/hour
Nvidia logoH100 SXM
217.89/hour
Nvidia logoA100 80GB
120.69/hour
Nvidia logoA100 40GB
104.49/hour
Nvidia logoRTX 6000 Ada
80.19/hour
Nvidia logoA6000
63.99/hour
Nvidia logoA5000
39.69/hour
Nvidia logoL4
35.64/hour
Storage
Instance Storage
0.0113/GB/hour

Prices shown in INR (1 USD = ₹81). Billing in USD at the displayed rate. Minute-level billing.

FAQ

Frequently Asked Questions

Can't find what you're looking for? Reach out to our support team.

The L4 starts at ₹35.64/hr, making it one of the most affordable options for inference and video workloads. The A5000 starts at ₹39.69/hr for training.

JarvisLabs offers volume discounts for teams and institutions. Contact us for pricing details on sustained usage.

No. You pay only for GPU compute time (per minute) and storage. No setup fees, no bandwidth charges, no minimum commitment.

JarvisLabs is typically 2-3x cheaper than AWS and GCP for equivalent GPU hardware, with simpler pricing and no reserved instance complexity.

Sign up, top-up your credits, select your preferred GPU (e.g., A100, H100), and launch your instance. Within minutes, you’ll have a fully configured environment ready for AI training or any GPU-accelerated workload.

We don’t offer a free trial, but you can start exploring with as little as $10. Our pay-as-you-go model ensures you only pay when you rent a GPU and use it.

You’re charged only for the time your rented GPU instance is running. When paused, you pay solely for storage. Our per-minute billing means no hidden fees or commitments.

A template is a pre-built container with a primary framework (e.g., PyTorch, TensorFlow). After you rent a GPU, you can install custom packages via apt or pip to suit your project.

Once you rent a GPU, instances typically launch in seconds. Start coding immediately via JupyterLab, VS Code Web, or SSH.

Your rented GPU instances run in isolated environments with private networking, ensuring proper data isolation and security.

Pausing stops GPU usage charges. You pay only for storage while it’s paused. Resume anytime to continue working where you left off.

Deletion is permanent, and data cannot be recovered. After deletion, no further charges apply.

We currently offer GPU rentals in India and Finland, with more regions coming soon.

We provide technical support related to the entire lifecycle of your rented GPU instance. While we do our best to address framework-specific queries, we can’t guarantee support for all open-source tools.

We use Stripe for secure payments. Pay with credit/debit cards or net banking, ensuring a smooth transaction process.

Not currently. We support Stripe transactions at this time.

We don’t offer refunds. If you have a valid reason, email us at support@jarvislabs.ai, and we’ll review your request.