Run ComfyUI in the cloud: hosted service or your own GPU

Pick the right kind of cloud

Comfy Cloud is the official managed service and requires no local installation. A rented GPU or Docker container you maintain is self-managed. Colab is a managed notebook runtime with its own policies and limits. These routes differ in runtime control, package versions, storage and network exposure. Review the official service's current price and supported model/node catalog before subscribing.

Managed route

Open Comfy Cloud, choose a template, provide inputs, run it and download results as described in the official guide. Check plan terms and data handling on the official service before uploading private material.

Self-hosted route

Start from the official manual install guide on the remote machine or in an image you maintain. Select the GPU-specific PyTorch build for that host, use an isolated Python environment, install ComfyUI requirements, and test locally on the host first. A Docker image adds container filesystem and volume choices; do not treat an arbitrary third-party image as official. Persist models, workflows and outputs outside an ephemeral container. Protect access with authentication or a private tunnel before making the UI reachable.

Colab and notebook cautions

Read the Colab FAQ for current resource, runtime and usage limits. A notebook runtime can be reset; explicitly save files you need. Google's free managed runtimes restrict using a web UI as the primary interaction instead of the notebook interface and may terminate such sessions; check current plan rules before attempting a ComfyUI web UI. Do not place credentials in a public notebook or promise a permanent GPU or URL. This guide does not supply an unverified one-click notebook.

Completion check

Confirm the actual host's GPU backend, load a small template, run it and verify that output survives the storage boundary you chose. The procedure is editorial guidance, not a tested deployment or guarantee of availability.