---
title: "Kaggle Free GPU and TPU Notebooks"
slug: "kaggle-free-gpu-tpu"
provider: "Kaggle"
status: "verified"
verifiedAt: "2026-10-12"
listedAt: "2026-09-12"
canonical: "https://aifree.dev/offer/kaggle-free-gpu-tpu"
---

# Kaggle Free GPU and TPU Notebooks

> Free Kaggle notebooks: 30 hours/week of GPU and 20 hours/week of TPU

- Provider: [Kaggle](https://aifree.dev/provider/kaggle-com)
- What is free: 30 hours/week
- Status: verified by a person on 2026-10-12
- Credit card: not required
- Sign-up: required
- For: Startups
- Resets: weekly
- Claim at: https://www.kaggle.com/code

## What you get

Kaggle accounts get free browser-based Jupyter notebooks with up to 30 hours per week of NVIDIA GPU time and 20 hours per week of TPU v3-8 time, with no paid plan required and 12-hour GPU and 9-hour TPU session limits.

## The catch

Phone verification is required to unlock GPU/TPU accelerators; weekly quotas reset weekly and can vary with demand, and sessions are capped at 9-12 hours.

## Limits

- Up to 30 hours/week GPU (resets weekly, sometimes higher with demand)
- Up to 20 hours/week TPU (TPU v3-8), 9-hour max session
- 12-hour max execution per CPU/GPU session
- Phone verification required to enable accelerators
- Accelerators: NVIDIA Tesla P100 (16GB), 2x NVIDIA T4, or TPU v3-8
- Colab Pro/Pro+ subscribers can add +15/+30 extra GPU hours/week

## Details

## Overview

[Kaggle](https://www.kaggle.com/code) provides free browser-based Jupyter notebooks with GPU and TPU accelerators. Compute is allocated through a weekly quota instead of a paid plan, and notebooks come with a pre-configured Python or R environment.

## Free Tier Quotas & Limits

Kaggle's documentation states:

- **GPU:** up to **30 hours per week**; the quota resets weekly and is "sometimes higher depending on demand and resources".
- **TPU:** up to **20 hours per week** on a TPU v3-8, with a maximum of 9 hours in a single session.
- **Session limits:** 12 hours execution time for CPU and GPU notebook sessions, 9 hours for TPU notebook sessions.
- **Accelerators:** one NVIDIA Tesla P100 (16 GB), two NVIDIA T4 GPUs (2 x 16 GB), or a TPU v3-8 with 8 cores and 128 GB of high-bandwidth memory.
- **Per-session resources:** 4 CPU cores with 29 GB RAM on GPU notebooks, 30 GB RAM on CPU notebooks, and 20 GB of auto-saved disk in `/kaggle/working`.
- Internet access can be enabled from the notebook settings pane. Free accelerator availability is limited, so busy periods can place sessions in a queue.

## How to Get Started

Register for a free account at [kaggle.com](https://www.kaggle.com), then open or create a notebook at [kaggle.com/code](https://www.kaggle.com/code) and pick an accelerator under Settings, Accelerator. For runs that outlast the browser, use "Save & Run All" so the notebook executes in a background session. Datasets can be attached read-only from `/kaggle/input`, and the Kaggle API allows notebooks to be pushed and executed from the command line.

## More

- HTML page: https://aifree.dev/offer/kaggle-free-gpu-tpu
- Change history: https://aifree.dev/offer/kaggle-free-gpu-tpu/history
- How it was verified: https://aifree.dev/offer/kaggle-free-gpu-tpu/verification
- More in [Free AI coding tools](https://aifree.dev/free-ai-coding-tools.md)
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