The AI Cloud.

Train, fine-tune, and serve models. Live in 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

Products

Three ways to run.

Same GPUs underneath. Pick how much of the stack you want to own.

On-Demand VMs

Root access, your stack

Root SSH from minute one
Your own Docker or Kubernetes
Custom kernels and drivers
Up to 8 GPUs, multi-region

Pick this when a container isn’t a machine.

Learn more

Templates

Managed containers

PyTorch, ComfyUI and more, pre-built
JupyterLab, VS Code, or SSH
Live in 1.8 seconds
Storage persists across stop / start

Pick this when you want to start training right away.

Learn more

ServerlessBeta

Endpoints that scale to zero

Deploy a model, get a URL
Autoscaling worker pool
Logs, metrics and usage built in
Pay per minute of worker runtime

Pick this when you’re serving, not training.

Platform

Built for teams.

Private networking, network file storage, and shared team billing. The layer under your workload, not an add-on.

What you get underneath

Private networkingYour own isolated VPC with IP ranges you choose.
Dedicated GPUsYour GPUs are never shared. On VMs you control the kernel, drivers and OS.
Network file storageOne filesystem, attached to as many of your own instances as you need.
Teams and billingAdmins manage members, allocate credits, and see team usage.
Data residencyChoose where your data lives. India and Europe today, more regions coming soon.

CLI & SDK

One interface.
Every product.

Drive templates, VMs, and deployments from the command line or Python — the same workflow across all three.

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

Pay by the minute with no minimum commitment, and only for storage while paused.

Explore Pricing

Hourly Pricing

GPUs

NVIDIA H200 SXM

$3.99/hour

NVIDIA H100 SXM

$2.69/hour

NVIDIA RTX Pro 6000

$1.89/hour

NVIDIA A100-80GB

$1.49/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.

A template is a managed container — we handle the OS, drivers, CUDA, and the runtime, and you bring your code. An On-Demand VM is a full machine with root access from minute one, so you can run your own Docker or Kubernetes, load custom kernels and drivers, and install anything a container can’t host. Both use the same GPUs at the same hourly rate.

Yes — launch an On-Demand VM. You get root SSH immediately and full control of the operating system, including custom kernel modules, your own container runtime, and your own monitoring or security agents.

Yes, currently in beta. Deploy a model and get an endpoint URL backed by an autoscaling worker pool that scales to zero when idle, with logs, metrics, and usage built in. Get in touch if you’d like access.

Yes. You can create a VPC with your own private IP ranges and run your instances inside it, isolated from other tenants’ traffic. VPCs are currently available in our India regions.

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 Europe, 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.

Get started

The AI Cloud.

Powering teams that push boundaries