How to use Kaggle's free TPU v5e-8: a 128 GB AI machine, step by step

Part 1

Set up your Kaggle account

1. 1

   Step 1: Create a free Kaggle account

   kaggle.com → then Register

   Choose Register with Google or Register with Email, whichever is easier. No card is needed.

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2. 2

   Step 2: Verify your phone number

   Profile picture → then Settings → then Phone verification

   Enter your number, then the code Kaggle texts you. When it's done, the section says Verified. Without this, notebooks get no TPU, no GPU and no internet.

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Part 2

Turn on the TPU and check it

1. 3

   Step 3: Create a new notebook

   + Create → then Notebook

   Click the + Create button on the left, then Notebook. A blank notebook opens.

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2. 4

   Step 4: Choose TPU v5e-8 as the accelerator

   Settings → then Accelerator → then ✓ TPU v5e-8

   Open Settings in the menu at the top of the notebook. Some screens call it TPU VM v5e-8; it's the same thing. The notebook restarts, and getting a TPU can take a few minutes.

   Internet must be on too, to download models. In the same menu, click Turn on internet if you see it. If it says Turn off internet, internet is already on.

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3. 5

   Step 5: Check that all 8 chips are there

   Type this in the first cell and press Shift + Enter:

   Notebook cell

   import jaxprint(jax.device_count())print(jax.devices()[0].device_kind)

   Output

   8
   TPU v5 lite

Part 3

Option A: run Qwen 27B (ready-made notebook)

Now run a large AI model on the TPU. There are two ways; pick one. A is the easiest: a ready-made notebook that gives you your own API. In B, Gemma 26B answers right inside the notebook. Both are public projects that have run on this same free TPU. The speed figures come from their READMEs; your run may differ a little.

1. 6

   Step 6: Copy the public Qwen notebook

   Open the notebook → then Copy & Edit

   Open Kiet Vo's public notebook: Qwen3.8-27B-bf16 for free on Kaggle TPU with API. Click Copy & Edit at the top; your own copy opens.

   In the copy, choose TPU v5e-8 under Accelerator and turn internet on, as in step 4.

2. 7

   Step 7: Check that both datasets are attached

   Right panel → then Input

   Open Input in the notebook's right panel. These two datasets should be there. They come attached with the copy; if one is missing, add it with Add Input by searching for its name.

   • rahim3/qwen3-8-27b-bf16: the model, 55.6 GB
   • rahim3/qwen38-tpu-env-v5e8: a ready-made compile cache
3. 8

   Step 8: Click Run All and wait about 22 minutes

   Run All

   The project's README says loading and compiling the model takes about 22 minutes. The last cell is the server: when it's ready, it prints a banner with a Base URL (…trycloudflare.com/v1), an API key (sk-…) and the model name qwen3.8-27b.

4. 9

   Step 9: Talk to the model

   Put the Base URL and API key into any OpenAI-compatible app, or run this curl command in a terminal. Replace the URL and key with your own:

   Terminal

   curl https://xxxx-yyyy.trycloudflare.com/v1/chat/completions \  -H "Authorization: Bearer sk-<your-key>" \  -H "Content-Type: application/json" \  -d '{"model":"qwen3.8-27b","messages":[{"role":"user","content":"Hi! Explain a TPU in one line."}]}'

Part 4

Option B: run Gemma 26B (JAX)

Here Google's Gemma 4 26B model answers right inside the notebook. No public URL is created.

1. 10

   Step 10: Create a Hugging Face read token

   huggingface.co → then Settings → then Access Tokens → then Create new token

   Create a free Hugging Face account, then create a token of type Read and copy it. The project's setup uses this token to download the model.

2. 11

   Step 11: Add the token to Kaggle Secrets

   Add-ons → then Secrets → then Add Secret

   Enter HF_TOKEN as the label, exactly as written, and your token as the value. After saving, tick the box next to the secret so this notebook can read it.

   This notebook also needs TPU v5e-8 and internet turned on, as in step 4.

3. 12

   Step 12: Run the setup (first time only)

   Run this in a new cell:

   Notebook cell

   %%bashcd /root && rm -rf kaggle-tpu-inference && \git clone https://github.com/YLiu95/kaggle-tpu-inference.git && \cd kaggle-tpu-inference && bash setup.sh

4. 13

   Step 13: Ask Gemma a question

   Run this cell as often as you like; just change the question in quotes:

   Notebook cell

   %%bashcd /root/kaggle-tpu-inference && \bash run.sh "Hi! Explain a TPU in one line." --max-new-tokens 768 --temperature 1.0

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