Google Colab Guides — GPUs, Drive, CLI, and Open-Weight Models

Practical Google Colab guides: get started with a paid Google AI plan, mount Drive, manage GPU runtimes and compute units, use the Colab CLI, and run Qwen-Image and MiniMax H3 in ComfyUI.

September 24, 2026
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Google Colab gives you a hosted Jupyter notebook backed by a temporary cloud virtual machine, with optional GPUs and TPUs. Since September 2026, eligible paid Google AI plans include Colab benefits — compute units and access to more powerful hardware — so a subscription you may already pay for doubles as a cloud workspace.

This section is a practical path through that setup, based on our own runs. The announcement blog post covers the news; these guides cover the doing.

Where to start

  1. Getting Started — confirm your plan's Colab benefits, create a notebook, connect, and choose a runtime.
  2. Working in Colab — the four skills you will use constantly: mounting Google Drive, inspecting GPUs and compute units, driving runtimes from the terminal with the Colab CLI, and reaching web UIs such as ComfyUI through proxies and tunnels.
  3. Hugging Face Models in Colab — choose the right model files, budget disk and VRAM, and download weights into the layout a workflow expects.

Model walkthroughs

Google Colab on a paid plan