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Runpod CLI to manage your GPU workloads.
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Basé sur la classification professionnelle SOC
| name | runpodctl |
| description | Runpod CLI to manage your GPU workloads. |
| allowed-tools | Bash(runpodctl:*) |
| compatibility | Linux, macOS |
| metadata | {"author":"runpod","version":"2.1"} |
| license | Apache-2.0 |
Manage GPU pods, serverless endpoints, templates, volumes, and models.
Spelling: "Runpod" (capital R). Command is
runpodctl(lowercase).
# Any platform (official installer)
curl -sSL https://cli.runpod.net | bash
# macOS (Homebrew)
brew install runpod/runpodctl/runpodctl
# macOS (manual — universal binary)
mkdir -p ~/.local/bin && curl -sL https://github.com/runpod/runpodctl/releases/latest/download/runpodctl-darwin-all.tar.gz | tar xz -C ~/.local/bin
# Linux
mkdir -p ~/.local/bin && curl -sL https://github.com/runpod/runpodctl/releases/latest/download/runpodctl-linux-amd64.tar.gz | tar xz -C ~/.local/bin
# Windows (PowerShell)
Invoke-WebRequest -Uri https://github.com/runpod/runpodctl/releases/latest/download/runpodctl-windows-amd64.zip -OutFile runpodctl.zip; Expand-Archive runpodctl.zip -DestinationPath $env:LOCALAPPDATA\runpodctl; [Environment]::SetEnvironmentVariable('Path', $env:Path + ";$env:LOCALAPPDATA\runpodctl", 'User')
Ensure ~/.local/bin is on your PATH (add export PATH="$HOME/.local/bin:$PATH" to ~/.bashrc or ~/.zshrc).
runpodctl doctor # First time setup (API key + SSH)
runpodctl gpu list # See available GPUs
runpodctl template search pytorch # Find a template
runpodctl pod create --template-id runpod-torch-v21 --gpu-id "NVIDIA RTX 4090" # Create from template
runpodctl pod list # List your pods
API key: https://runpod.io/console/user/settings
runpodctl pod list # List running pods (default, like docker ps)
runpodctl pod list --all # List all pods including exited
runpodctl pod list --status exited # Filter by status (RUNNING, EXITED, etc.)
runpodctl pod list --since 24h # Pods created within last 24 hours
runpodctl pod list --created-after 2025-01-15 # Pods created after date
runpodctl pod get <pod-id> # Get pod details (includes SSH info)
runpodctl pod create --template-id runpod-torch-v21 --gpu-id "NVIDIA RTX 4090" # Create from template
runpodctl pod create --image "runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel-ubuntu22.04" --gpu-id "NVIDIA RTX 4090" # Create with image
runpodctl pod create --compute-type cpu --image ubuntu:22.04 # Create CPU pod
runpodctl pod start <pod-id> # Start stopped pod
runpodctl pod stop <pod-id> # Stop running pod
runpodctl pod restart <pod-id> # Restart pod
runpodctl pod reset <pod-id> # Reset pod
runpodctl pod update <pod-id> --name "new" # Update pod
runpodctl pod delete <pod-id> # Delete pod (aliases: rm, remove)
List flags: --all / -a, --status, --since, --created-after, --name, --compute-type
Get flags: --include-machine, --include-network-volume
Create flags: --template-id (required if no --image), --image (required if no --template-id), --name, --gpu-id, --gpu-count, --compute-type, --ssh (default true), --container-disk-in-gb, --volume-in-gb, --volume-mount-path, --ports, --env, --cloud-type, --data-center-ids, --global-networking, --public-ip
runpodctl serverless list # List all endpoints
runpodctl serverless get <endpoint-id> # Get endpoint details
runpodctl serverless create --name "x" --template-id "tpl_abc" # Create endpoint
runpodctl serverless update <endpoint-id> --workers-max 5 # Update endpoint
runpodctl serverless delete <endpoint-id> # Delete endpoint
List flags: --include-template, --include-workers
Update flags: --name, --workers-min, --workers-max, --idle-timeout, --scaler-type (QUEUE_DELAY or REQUEST_COUNT), --scaler-value
Create flags: --name, --template-id, --gpu-id, --gpu-count, --compute-type, --workers-min, --workers-max, --data-center-ids
runpodctl template list # Official + community (first 10)
runpodctl template list --type official # All official templates
runpodctl template list --type community # Community templates (first 10)
runpodctl template list --type user # Your own templates
runpodctl template list --all # Everything including user
runpodctl template list --limit 50 # Show 50 templates
runpodctl template search pytorch # Search for "pytorch" templates
runpodctl template search comfyui --limit 5 # Search, limit to 5 results
runpodctl template search vllm --type official # Search only official
runpodctl template get <template-id> # Get template details (includes README, env, ports)
runpodctl template create --name "x" --image "img" # Create template
runpodctl template create --name "x" --image "img" --serverless # Create serverless template
runpodctl template update <template-id> --name "new" # Update template
runpodctl template delete <template-id> # Delete template
List flags: --type (official, community, user), --limit, --offset, --all
Create flags: --name, --image, --container-disk-in-gb, --volume-in-gb, --volume-mount-path, --ports, --env, --docker-start-cmd, --docker-entrypoint, --serverless, --readme
runpodctl network-volume list # List all volumes
runpodctl network-volume get <volume-id> # Get volume details
runpodctl network-volume create --name "x" --size 100 --data-center-id "US-GA-1" # Create volume
runpodctl network-volume update <volume-id> --name "new" # Update volume
runpodctl network-volume delete <volume-id> # Delete volume
Create flags: --name, --size, --data-center-id
runpodctl model list # List your models
runpodctl model list --all # List all models
runpodctl model list --name "llama" # Filter by name
runpodctl model list --provider "meta" # Filter by provider
runpodctl model add --name "my-model" --model-path ./model # Add model
runpodctl model remove --name "my-model" # Remove model
runpodctl registry list # List registry auths
runpodctl registry get <registry-id> # Get registry auth
runpodctl registry create --name "x" --username "u" --password "p" # Create registry auth
runpodctl registry delete <registry-id> # Delete registry auth
runpodctl user # Account info and balance (alias: me)
runpodctl gpu list # List available GPUs
runpodctl gpu list --include-unavailable # Include unavailable GPUs
runpodctl datacenter list # List datacenters (alias: dc)
runpodctl billing pods # Pod billing history
runpodctl billing serverless # Serverless billing history
runpodctl billing network-volume # Volume billing history
runpodctl ssh info <pod-id> # Get SSH info (command + key, does not connect)
runpodctl ssh list-keys # List SSH keys
runpodctl ssh add-key # Add SSH key
Agent note: ssh info returns connection details, not an interactive session. If interactive SSH is not available, execute commands remotely via ssh user@host "command".
runpodctl send <path> # Send files (outputs code)
runpodctl receive <code> # Receive files using code
runpodctl doctor # Diagnose and fix CLI issues
runpodctl update # Update CLI
runpodctl version # Show version
runpodctl completion bash >> ~/.bashrc # Install bash completion
runpodctl completion zsh >> ~/.zshrc # Install zsh completion
Access exposed ports on your pod:
https://<pod-id>-<port>.proxy.runpod.net
Example: https://abc123xyz-8888.proxy.runpod.net
https://api.runpod.ai/v2/<endpoint-id>/run # Async request
https://api.runpod.ai/v2/<endpoint-id>/runsync # Sync request
https://api.runpod.ai/v2/<endpoint-id>/health # Health check
https://api.runpod.ai/v2/<endpoint-id>/status/<job-id> # Job status
Use for deeper DDD decisions: strategic modeling, subdomains, bounded contexts, and integration risk.
Use when complexity is spreading and you need a simpler model, clearer abstractions, and lower cognitive load.
Use for boundary design, dependency direction, and keeping business policy separate from technical detail.
Use for readability, naming, small functions, and readable behavior-preserving implementations.
Use for disciplined implementation decisions, defensive coding, and maintainable construction choices in real code.
Use when moving from model intent into concrete tactical patterns, events, and distributed integration choices.