The AI Cloud.

Train, fine-tune, and serve models. Live in 90 seconds, pay by the minute.

fromH200$3.99·H100$2.69·RTX Pro 6000$1.89/hr

~/project

$ █

Explore the CLI

Trusted worldwide

Powering teams that push boundaries

27,000+AI developers

50M+GPU hours served

99.9%Uptime SLA

<90sInstance launch

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.

H200H100A100RTX Pro 600020GB–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

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

~/projectCLI demo

$ 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

Explore the CLI

Testimonials

Loved by AI Practitioners

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

“

“The cheapest would probably be Jarvis Labs. They're very popular in our community. https://jarvislabs.ai”

Jeremy Howard

Founder, fast.ai

“

“Looking to run a bigger model on GPU at a cheaper price, give @jarvislabsai a try and thank me later 😀 Got my machine up and running in a few mins 🔥 Thank you @vishnuvig!”

SRK

@sudalairajkumar

“

“If you haven't tried http://jarvislabs.ai you should. Fast start times, well priced, simple UI, easy billing. I have always chosen between config crap, expensive price, or long launch times. This is the first platform that I've seen that I think gets all of these items right!”

Isaac Flath

@isaac_flath

“

“The incredible https://jarvislabs.ai by @vishnuvig IMO offers one of the best pricing for renting compute 💰 TIL that they are completely bootstrapped & operate out of India! 🙏 It's really fulfilling to hear one of the best startups from @fastdotai classroom is from the country!”

Sanyam Bhutani

@bhutanisanyam1

“

“@jarvislabsai is the best GPU cloud provider for DL practitioners out there, period. More than once I had a question and support helped me in minutes, not only fast but so so friendly...”

Lucas Vazquez

@vzzqzzz

“

“Addict to @jarvislabsai. Less branded than others on the surface but super simple. Great GPUs (training on 8 x A100s is amazing). This beats Paperspace premium accounts, Colab with custom VMs... I loved RunwayML as well ...”

Laurent Thevenet

@thelau

Pricing

Pay as you go

Our pricing model lets you pay only for what you use. Choose from the latest NVIDIA GPUs like H100 and A100 at competitive hourly rates, with no minimum commitments. Paused instances only incur storage fees.

GPU rental starts from $0.41/hr

Explore Pricing

GPU Rental Pricing

GPUs

H200 SXM

$3.99/hour

H100 SXM

$2.69/hour

RTX Pro 6000

$1.89/hour

A100-80GB

$1.49/hour

A100

$0.89/hour

L4

$0.44/hour

A30

$0.41/hour

Storage

Instance Storage

$0.00014/GB/hour

FAQ

Frequently Asked Questions

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

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 [email protected], and we’ll review your request.

Get started

The AI Cloud.

Powering teams that push boundaries