CH·02CLI reference

gpu deploy

Deploy a curated application template onto a GPU instance

Synopsis

Deploys a curated application template (e.g. comfyui, automatic1111, vllm, faster-whisper, axolotl-finetuning) onto a GPU instance. A template deploy *is* an instance — it reuses the same async operation FSM as gpu instances create. The cheapest eligible GPU is auto-selected unless you pass --type.

The CLI polls the operation until the app is ready (10-minute deadline by default), then prints the instance details plus the app's HTTPS URL — your app is reachable at https://.apps.gpu.ai behind HTTP basic-auth. The basic-auth username and password are surfaced exactly once on deploy.

⚠ The app password is shown once on deploy and cannot be retrieved later. Save it when you see it.

Use --wait-timeout=0 to skip polling and print just the operation_id for scripts that poll asynchronously.

For templates that serve a Hugging Face model via --env MODEL=… (vLLM, SGLang), the API checks the model's published weights size against the GPU's VRAM at submit time: an oversized model on an explicit --type is rejected immediately with an actionable 422 model_too_large (rather than crash-looping until the provisioning timeout), and auto-select raises its VRAM floor so placement lands on a GPU the model fits. Gated/private/unknown repos are never blocked — the deploy proceeds and the CLI prints a Warning: line that the size could not be verified. See deployable-templates.md.

gpu deploy <template-id> [flags]

Examples

# Deploy ComfyUI (auto-selects the cheapest eligible GPU)
gpu deploy comfyui --tier on_demand --ssh-key-id <key-id>

# vLLM with a model + HF token (secret env is redacted from logs/metadata)
gpu deploy vllm --env MODEL=meta-llama/Llama-3.1-8B-Instruct --env HF_TOKEN=hf_xxx

# Axolotl fine-tuning workbench (Jupyter Lab) — HF token unlocks gated models
gpu deploy axolotl-finetuning --env HF_TOKEN=hf_xxx

# Faster Whisper speech-to-text (web UI + OpenAI-compatible audio API; zero config)
gpu deploy faster-whisper --tier on_demand --ssh-key-id <key-id>

# Stable Diffusion WebUI (A1111) — extra webui flags via A1111_ARGS
gpu deploy automatic1111 --env A1111_ARGS="--enable-insecure-extension-access"

# Pin a GPU type instead of auto-selecting
gpu deploy comfyui --type h100_sxm --ssh-key-id <key-id>

# Don't wait — just submit and print operation_id
gpu deploy comfyui --wait-timeout 0

Options

      --env stringToString        Env override KEY=VALUE (may repeat); only user-overridable keys are accepted
  -h, --help                      help for deploy
      --name string               Optional instance name
      --region string             Region (e.g., us-east); empty = any
      --ssh-key-id strings        SSH key ID to inject (may repeat)
      --tier string               Tier: on_demand | spot (default "on_demand")
  -t, --type string               GPU type ID override (e.g., h100_sxm); empty = auto-select cheapest eligible
      --wait-timeout duration     How long to poll the operation; 0 = don't poll, just print operation_id (default 10m0s)

Options inherited from parent commands

      --api-base string   API base URL (override with GPUAI_API_BASE env) (default "https://api.gpu.ai/v1")
      --debug             Enable debug logging to stderr
  -o, --output string     Output format: table|json (default table on TTY, json otherwise)

Synopsis

Examples

Options

Options inherited from parent commands

SEE ALSO