Kaggle Free GPU and TPU Notebooks
Free Kaggle notebooks: 30 hours/week of GPU and 20 hours/week of TPU
What you get from Kaggle Free GPU and TPU Notebooks for free
Overview
Kaggle 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, then open or create a notebook at 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.
Before you claim
- Startups verification: Confirm your company details (age, funding, or website) to claim.
- Payment card: Not needed.
- Account: Sign up with the provider.
Key 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
History
Verified by a person on · last automated check : the page could not be read automatically. Automated findings never change this page until a person confirms them (how we verify).
- Terms updatedby a person · Content updated from https://www.kaggle.com/docs/tpu (checked 2026-10-20).
- Verifiedby a person
- Listedby a person
Full history with screenshots · How we verified this offer · Sitewide changelog
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A few minutes of play-along, no sign-up.
- Why does a 7B model need 16 GB of RAM? · Model memory: parameters × bytes, plus the KV cache · 5 min
- How can I fine-tune a model on a free GPU? · LoRA and QLoRA: train small matrices beside frozen weights · 5 min
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