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What you can do with Kaggle Tpu Lab

A set of notebooks and scripts that run open AI models on Kaggle's free TPU v5e-8 and expose them as a public endpoint that speaks the OpenAI and Anthropic APIs.

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ARahim3/kaggle-tpu-lab on GitHub

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What do you want to do?

5 use cases

  • Run a free open model as an endpoint for Claude Code

    Start a Kaggle notebook, copy the public URL and key, and point Claude Code at an open model.

    View prompt
    In the ARahim3/kaggle-tpu-lab repo, open the Qwen3.8-27B notebook from the model table, run it on Kaggle, and copy the printed URL and API key into ANTHROPIC_BASE_URL and ANTHROPIC_AUTH_TOKEN, with ANTHROPIC_MODEL set to <model>. Expected output: a Claude Code reply to a test prompt from the open model. Verify that the endpoint answers before reporting success.

  • Point Codex CLI at a Kaggle-hosted open model

    Use the public endpoint from a Kaggle TPU session as the backend for Codex CLI.

    View prompt
    In the ARahim3/kaggle-tpu-lab repo, read the Codex CLI lines in the <model> folder README, run that model's notebook on Kaggle, and configure Codex CLI with the printed URL and API key. Expected output: a Codex CLI answer to a test question served from the TPU. Verify the request reaches the Kaggle endpoint, not a default provider.

  • Launch a model server from the terminal

    Clone the repo and start the Qwen3.8-27B serve recipe from your command line.

    View prompt
    Clone ARahim3/kaggle-tpu-lab, run `python launch.py serve` to start the default model, and use `python launch.py status` until the server reports ready. Expected output: a running Kaggle TPU session with a public URL. Verify the status output shows the session active before handing the URL to <target>.

  • Run GLM-5.3-Flash on a rented Google Cloud TPU VM

    Use the gcp/ guide and scripts to serve GLM-5.3-Flash without the Kaggle queue or time cap.

    View prompt
    In the ARahim3/kaggle-tpu-lab repo, follow the gcp/ guide to set up a v5litepod-8 or v6e-8 TPU VM, run the environment, datasets and run scripts, and serve GLM-5.3-Flash. Expected output: a running server on the TPU VM. Verify the server responds to one test request before reporting success.

  • Add a new model recipe to the repo

    Create a model folder with a README, kernel script and notebook following the repo's layout.

    View prompt
    In the ARahim3/kaggle-tpu-lab repo, add a new top-level folder for <model> with README.md, kernel/ and notebook/ following the Adding a model section and the existing folders. Expected output: a new folder whose notebook runs on Kaggle TPU and serves the model. Verify the config block matches between the launcher and the notebook.

How to use Kaggle Tpu Lab

  1. Check you have what it needs: A Kaggle account with TPU access, verified under Settings (phone number, and for some accounts a Persona identity check); Kaggle's free TPU quota, around 20 TPU hours a week; For the terminal route: Python 3.9+ and the Kaggle CLI.
  2. Open ARahim3/kaggle-tpu-lab on GitHub and read the README and license.
  3. Open the Qwen3.8-27B or GLM-5.3-Flash notebook linked in the model table of the README and click Run all.
  4. Wait for the last cell to print the public URL and an API key, then leave that cell running.
  5. Set the variables from the README in your shell: ANTHROPIC_BASE_URL=<url> ANTHROPIC_AUTH_TOKEN=<key> ANTHROPIC_MODEL=<model> followed by claude. (inferred, check the README)
  6. Send a short test prompt in Claude Code and confirm a reply comes back from the endpoint.

These steps come from our top use case, Run a free open model as an endpoint for Claude Code, which also has a copy-paste agent prompt.

Kaggle Tpu Lab alternatives · Best AI repos for Software and DevOps

About this repo

Requirements

  • A Kaggle account with TPU access, verified under Settings (phone number, and for some accounts a Persona identity check)
  • Kaggle's free TPU quota, around 20 TPU hours a week
  • For the terminal route: Python 3.9+ and the Kaggle CLI
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Questions about Kaggle Tpu Lab

What is Kaggle Tpu Lab?

A set of notebooks and scripts that run open AI models on Kaggle's free TPU v5e-8 and expose them as a public endpoint that speaks the OpenAI and Anthropic APIs. It is an open-source project on GitHub: https://github.com/ARahim3/kaggle-tpu-lab.

Who is Kaggle Tpu Lab for?

Developers and AI-agent users who want a free, large open model behind their coding agent without a GPU or cloud bill.

What can I do with Kaggle Tpu Lab?

5 use cases so far, for example: Run a free open model as an endpoint for Claude Code; Point Codex CLI at a Kaggle-hosted open model; Launch a model server from the terminal. Each has steps and a copy-paste agent prompt.

What do I need to run Kaggle Tpu Lab?

A Kaggle account with TPU access, verified under Settings (phone number, and for some accounts a Persona identity check); Kaggle's free TPU quota, around 20 TPU hours a week; For the terminal route: Python 3.9+ and the Kaggle CLI.

What are alternatives to Kaggle Tpu Lab?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Kaggle Tpu Lab safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.