Kaggle Notebooks

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What Kaggle Notebooks is

Kaggle Notebooks is a free cloud environment for reproducible, collaborative machine learning analysis. Notebooks use Jupyter cells and can also be written as sequential scripts in Python or R. Sessions run in Docker containers with pre-installed packages and customizable compute resources. Users can attach public datasets, upload their own data, use outputs from other notebooks, or combine several sources in one environment. A free NVIDIA Tesla P100 GPU or TPU v3-8 can be added, though availability is limited and queues may occur. Saving and running a notebook creates a version snapshot that records code, outputs, data sources, logs, and environment metadata. Runs can be scheduled daily, weekly, monthly, or when an associated dataset changes; dataset-triggered runs occur at most once a day. Integrations include Google Cloud Storage, BigQuery, and AutoML. Editors such as Colab and VS Code can connect to a Kaggle Jupyter Server. CPU and GPU sessions are limited to 12 hours, TPU sessions to 9 hours, and interactive sessions to 20 minutes idle time.

Who it suits

Kaggle Notebooks suits people doing collaborative machine learning analysis in Python or R, especially those who want hosted compute, attached datasets, and saved notebook versions. It can also suit users scheduling runs or connecting from supported editors.

What it does well

Free cloud notebook environment with Python and R.
Saved runs capture code, outputs, sources, logs, and environment details.
Supports scheduled runs and dataset-triggered runs.
Editors including Colab and VS Code can connect.

What to know first

Free GPU and TPU availability is limited and may queue.
CPU and GPU sessions are limited to 12 hours.
TPU sessions are limited to 9 hours.
Interactive sessions have 20 minutes of idle time.

Limits

The free plan costs nothing and includes 20 GB autosaved disk. Free P100 GPU and TPU v3-8 availability is limited and may queue; CPU and GPU sessions are limited to 12 hours, TPU sessions to 9 hours, and interactive sessions to 20 minutes idle time.

Plans

Plan	Billed and limits	Price
Kaggle Notebooks	Free P100 GPU and TPU v3-8 availability is limited and may queue · CPU/GPU sessions up to 12 hours; TPU sessions up to 9 hours · 20 GB autosaved disk	Free
Kaggle Notebooks free	12-hour CPU/GPU sessions · 9-hour TPU sessions · 20 GB auto-saved working disk · weekly GPU quota usually 30 hours or higher · GPU availability can queue	Free

As kaggle.com lists them, read 2 Oct 2026. The maker's own page has the final word.

Getting started

Visit https://www.kaggle.com/code.
Create or open a notebook in the Jupyter-cell editor, or write a sequential Python or R script.
Attach public data, upload data, use another notebook’s outputs, or add multiple sources.
Choose a Kaggle Model from its detail page’s Code menu to attach it, if needed.
Select available compute resources; free P100 GPU and TPU v3-8 availability is limited.
Save and run the notebook to create a version snapshot.

Verdict

Kaggle Notebooks combines hosted Python and R workspaces with saved versions, data attachments, and scheduling. Its free compute has availability and session limits to consider for longer or interactive tasks.

Questions

How much does Kaggle Notebooks cost?

The listed plan is free.

Is there a free plan?

Yes. The listed plan includes free P100 GPU and TPU v3-8 availability, which is limited and may queue.

Which languages does it support?

It supports Python and R, including Jupyter-cell notebooks and sequential scripts.

What platforms are listed?

The listed platforms are web and API.

Can I schedule notebook runs?

Yes. Runs can be scheduled daily, weekly, monthly, or when an associated dataset changes. Dataset-triggered runs occur at most once per day.

What are the session limits?

CPU and GPU sessions are limited to 12 hours, TPU sessions to 9 hours, and interactive sessions to 20 minutes idle time.

Facts from Kaggle Notebooks's own pages

Acquisition news: TechCrunch reported on March 8, 2017 that Google confirmed its acquisition of Kaggle and did not disclose deal terms. · techcrunch.com, 14 Oct 2026
API: Kaggle provides a command-line interface for interacting with the platform through terminal commands or shell scripts. · kaggle.com, 2 Oct 2026
CLI licence: The official Kaggle CLI is released under the Apache 2.0 licence. · github.com, 14 Oct 2026
Company founders: Crunchbase lists Anthony Goldbloom and Ben Hamner as founders. · crunchbase.com, 14 Oct 2026
Company founding: LinkedIn lists Kaggle as founded in 2010. · linkedin.com, 14 Oct 2026
Company headquarters: LinkedIn lists San Francisco, California as headquarters. · linkedin.com, 14 Oct 2026
Company legal name: Crunchbase lists the legal name as Kaggle Inc. · crunchbase.com, 14 Oct 2026
Company ownership: Crunchbase identifies Kaggle as a Google sub-organization acquired by Google. · crunchbase.com, 14 Oct 2026
Company size: LinkedIn lists Kaggle's company size as 11–50 employees. · linkedin.com, 14 Oct 2026
Compliance enforcement: Kaggle states that it has removed thousands of competition teams for rule violations and does not disclose detection information to prevent evasion. · kaggle.com, 14 Oct 2026
Compute: Users can add a free NVIDIA Tesla P100 GPU or TPU v3-8, subject to limited availability and possible queues. · kaggle.com, 2 Oct 2026
Compute specifications: Documented environments include four CPU cores with about 30 GB RAM; P100 and dual-T4 GPU options; and a TPU 1VM with 96 CPU cores and 330 GB RAM. · kaggle.com, 14 Oct 2026
Data sources: Users can attach public data sources, upload their own data, use outputs from other notebooks, and add multiple sources to one environment. · kaggle.com, 2 Oct 2026
Dependency management: Kaggle’s Dependency Manager installs external Python packages and saves their versions for reuse. · kaggle.com, 2 Oct 2026
Dependency manager: A Dependency Manager installs pip packages, including packages directly from GitHub, and creates an installation notebook for commits. · kaggle.com, 14 Oct 2026
Documentation depth: Official documentation covers notebooks, packages, GPU usage, TPU usage, models, API access, benchmarks, scheduling, and Jupyter Server connections. · kaggle.com, 14 Oct 2026
Editor connections: Users can connect to a Kaggle Jupyter Server from editors including Colab and VS Code. · kaggle.com, 2 Oct 2026
Environment: Notebook sessions run in Docker containers with pre-installed packages and customizable compute resources. · kaggle.com, 2 Oct 2026
External editors: Users can connect Kaggle Jupyter Servers to Colab or VS Code through a Colab-compatible URL. · kaggle.com, 14 Oct 2026
Free plan: Yes · kaggle.com, 20 Sept 2026
GPU accelerator: Kaggle provides free NVIDIA Tesla P100 GPU access, with weekly quota commonly 30 hours or more. · kaggle.com, 14 Oct 2026
HIPAA limitation: Kaggle's terms say the service is not intended to create HIPAA obligations and makes no representation that it satisfies HIPAA requirements. · kaggle.com, 14 Oct 2026
Idle timeout: Interactive editing sessions end after 20 minutes without code changes or execution. · kaggle.com, 14 Oct 2026
Integrations: Kaggle Notebooks integrates with Google Cloud Storage, BigQuery, and AutoML through the editor’s Google Cloud Services add-on. · kaggle.com, 2 Oct 2026