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Guides
Deploy your first RunPod
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Cloud-Hosting
Easy

Deploy your first RunPod

Learn how to create a RunPod account, deploy your first GPU Pod, and execute code remotely in minutes.

15 min
RunPod
Cloud
GPU
Getting Started

Deploy your first Pod

RunPod Banner
RunPod Logo

Run code on a remote GPU in minutes with RunPod's cloud infrastructure.

What You'll Learn

By the end of this guide, you'll have:

  • A RunPod account created and configured
  • Your first GPU Pod deployed and running
  • Experience executing code on remote GPUs
  • Understanding of Pod management basics

Step 1: Create an account

1
Set Up Your RunPod Account

Create and configure your RunPod account:

  1. Sign up: Visit the RunPod signup page
  2. Verify email: Complete email verification
  3. Enable 2FA: Set up two-factor authentication (recommended for security)
Pro Tip

Planning to share compute resources with your team? You can convert your personal account to a team account later. See Manage accounts for details.

Step 2: Deploy a Pod

2
Launch Your First GPU Pod

Deploy your first Pod with these steps:

  1. Navigate to Pods: Open the Pods page in the web interface
  2. Start deployment: Click the Deploy button
  3. Select GPU: Choose A40 from the list of graphics cards
  4. Name your Pod: In the Pod Name field, enter quickstart-pod
  5. Keep defaults: Leave all other fields (Pod Template, GPU Count, and Instance Pricing) on their default settings
  6. Deploy: Click Deploy On-Demand to deploy and start your Pod
Payment Setup

If you haven't set up payments yet, you'll be prompted to add a payment method and purchase credits for your account.

Step 3: Explore the Pod detail pane

3
Familiarize Yourself with Pod Interface

Understanding the Pod interface helps you manage your resources effectively.

Access Pod Details:

  • On the Pods page, click your newly created Pod
  • The Pod detail pane opens to the Connect tab by default
  • Wait for initialization to complete before connecting

Explore the Interface Tabs:

  • Details: Hardware specs, pricing information, and storage details
  • Telemetry: Real-time utilization metrics for CPU, memory, and storage
  • Logs: Container logs and Pod management system output
  • Template Readme: Information about your Pod's template configuration
Pod Template

Your Pod is configured with the latest official RunPod PyTorch template, which includes common ML frameworks pre-installed.

Step 4: Execute code on your Pod with JupyterLab

4
Run Your First Code

Execute code on your remote GPU using JupyterLab:

  1. Open JupyterLab: In the Connect tab, under HTTP Services, click Jupyter Lab
  2. Create notebook: Under Notebook, select Python 3 (ipykernel)
  3. Write code: Type print("Hello, world!") in the first cell
  4. Execute: Click the play button to run your code
Congratulations!

You just ran your first line of code on RunPod! Your Pod is now ready for more complex workloads.

Step 5: Clean up

5
Manage Pod Resources

Properly managing your Pods prevents unnecessary charges.

Stop Your Pod:

  1. Return to Pods page: Navigate to the Pods page
  2. Select Pod: Click your running Pod
  3. Stop: Click the Stop button (pause icon)
  4. Confirm: Click Stop Pod in the confirmation modal
Storage Costs

Stopped Pods still incur storage charges (~$0.20 per GB per month). If you don't need the data, terminate the Pod completely.

Terminate Your Pod:

  1. Click Terminate: Click the Terminate button (trash icon)
  2. Confirm deletion: Click Terminate Pod to confirm
Data Loss Warning

Terminating a Pod permanently deletes all data that isn't stored in a network volume. Save any important data before terminating.

For more information about storage, see the Pod storage overview.

Next Steps

Now that you've mastered the basics of RunPod, you're ready to:

  • Generate API keys for programmatic resource management
  • Experiment with accessing and managing RunPod resources
  • Learn how to choose the right Pod for your workload
  • Review Pod pricing options to optimize costs
  • Explore tutorials for specific AI/ML use cases
  • Start building production applications with RunPod Serverless
  • Check out our ComfyUI on RunPod guide for AI image generation

Need Help?

Get support from the RunPod community:

  • Discord: Join the RunPod community on Discord
  • Support: Submit a request via our contact page
  • Email: Reach out directly at help@runpod.io

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