Colaboratory

Frequently Asked Questions

The Basics

What is Colaboratory?

Colaboratory, or “Colab” for short, is a product from Google Research. Colab allows anybody to write and execute arbitrary python code through the browser, and is especially well suited to machine learning, data analysis and education. More technically, Colab is a hosted Jupyter notebook service that requires no setup to use, while providing access free of charge to computing resources including GPUs.

Is it really free of charge to use?

Yes. Colab is free of charge to use.

Seems too good to be true. What are the limitations?

In order to provide access to as many students and under-resourced groups around the world as possible, Colab prioritizes users who are actively programming in a notebook. Colab also restricts actions that negatively impact others or are associated with bypassing our anti-abuse policies. See Which activities are restricted in Colab? for a list of actions that are disallowed. Colab resources are not guaranteed and not unlimited, and usage limits sometimes fluctuate. This is necessary for Colab to be able to provide resources free of charge. For more details, see Resource Limits.

Which activities are restricted in Colab?

Colab managed runtimes prohibit abusive actions that negatively impact others and actions associated with bypassing our policies. The following are disallowed from all managed Colab runtimes:

Unfortunately it is not possible to provide more specificity in how our abuse detection system works as bad actors try to take advantage of the compute subsidies Colab offers.

In addition to these restrictions, and in order to provide access to students and under-resourced groups around the world, Colab prioritizes users who are actively programming in a notebook. The following are disallowed from managed Colab runtimes running free of charge, without a positive Colab compute unit balance, and may be terminated at any time without warning:

You can remove these types of restrictions by purchasing one of our paid plans here and maintaining a positive compute unit balance. You may find not all runtimes that match the descriptions are terminated; we attempt to support as much as we can within reason to benefit the global community.

You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches.

Why does my Colab runtime keep terminating prematurely?

In order to provide access to students and under-resourced groups around the world, Colab prioritizes users who are actively programming in a notebook.

Users in our free of charge tier commonly experience runtime terminations when attempting to bypass the notebook UI and using a web UI on a Colab managed runtime for content generation. These experiences are popular and impressive, but are compute intensive and fall outside our priorities for our free of charge tier users, who we want to help in programming.

You can remove these types of restrictions by purchasing one of our paid plans here.

You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches.

What is the difference between Jupyter and Colab?

Jupyter is the open source project on which Colab is based. Colab allows you to use and share Jupyter notebooks with others without having to download, install, or run anything.

Using Colab

Where are my notebooks stored, and can I share them?

Colab notebooks are stored in Google Drive, or can be loaded from GitHub. Colab notebooks can be shared just as you would with Google Docs or Sheets. Simply click the Share button at the top right of any Colab notebook, or follow these Google Drive file sharing instructions.

If I share my notebook, what will be shared?

If you choose to share a notebook, the full contents of your notebook (text, code, output, and comments) will be shared. You can omit code cell output from being saved or shared by using Edit > Notebook settings > Omit code cell output when saving this notebook. The virtual machine you’re using, including any custom files and libraries that you’ve setup, will not be shared. So it’s a good idea to include cells which install and load any custom libraries or files that your notebook needs.

Can I import an existing Jupyter/IPython notebook into Colab?

Yes. Choose "Upload notebook" from the File menu.

How can I search Colab notebooks?

You can search Colab notebooks using Google Drive. Clicking on the Colab logo at the top left of the notebook view will show all notebooks in Drive. You can also search for notebooks that you have opened recently using File > Open notebook.

Where is my code executed? What happens to my execution state if I close the browser window?

Code is executed in a virtual machine private to your account. Virtual machines are deleted when idle for a while, and have a maximum lifetime enforced by the Colab service.

How can I get my data out?

You can download any Colab notebook that you’ve created from Google Drive following these instructions, or from within Colab’s File menu. All Colab notebooks are stored in the open source Jupyter notebook format ( .ipynb).

How can I reset the virtual machine(s) my code runs on, and why is this sometimes unavailable?

Selecting Runtime > Disconnect and delete runtime to return all managed virtual machines assigned to you to their original state. This can be helpful in cases where a virtual machine has become unhealthy e.g. due to accidental overwrite of system files, or installation of incompatible software. Colab limits how often this can be done to prevent undue resource consumption. If an attempt fails, please try again later.

Why does drive.mount() sometimes fail saying "timed out", and why do I/O operations in drive.mount()-mounted folders sometimes fail?

Google Drive operations can time out when the number of files or subfolders in a folder grows too large. If thousands of items are directly contained in the top-level "My Drive" folder then mounting the drive will likely time out. Repeated attempts may eventually succeed as failed attempts cache partial state locally before timing out. If you encounter this problem, try moving files and folders directly contained in "My Drive" into sub-folders. A similar problem can occur when reading from other folders after a successful drive.mount(). Accessing items in any folder containing many items can cause errors like OSError: [Errno 5] Input/output error. Again, you can fix this problem by moving directly contained items into sub-folders.
Note that "deleting" files or subfolders by moving them to the Trash may not be enough; if that doesn't seem to help, make sure to also Empty your Trash.

Why does "Mount Drive" sometimes insert code into the notebook?

Mounting Google Drive on Colab allows any code in your notebook to access any files in your Google Drive. We usually require that users manually grant this access every time they connect to a new runtime by adding a code cell to the notebook. This ensures that the user fully understands the permissions being granted to the notebook.
In some cases, we only require Google Drive authorization once, and automatically re-mount Google Drive during future sessions. To protect your files, we only allow this when a notebook passes multiple checks. For example, any notebooks which have been edited by another user do not automatically mount Google Drive.

Why do Drive operations sometimes fail due to quota?

Google Drive enforces various limits, including per-user and per-file operation count and bandwidth quotas. Exceeding these limits will trigger Input/output error as above, and show a notification in the Colab UI. A typical cause is accessing a popular shared file, or accessing too many distinct files too quickly. Workarounds include:

Why do Drive operations sometimes fail due to storage quota?

Google Drive imposes a limit on how much data can be stored in it by each user. If Drive operations are failing withInput/output error and a notification says storage quota has been exceeded, delete some files using drive.google.com and Empty your Trash to reclaim the space. It might take a little while for the reclaimed space to be available in Colab.

If you'd like to purchase more Drive space, visit Google Drive. Note that purchasing more space on Drive will not increase the amount of disk available on Colab VMs. Subscribing to Colab Pro will.

Resource Limits

Why aren’t resources guaranteed in Colab?

In order to dynamically offer powerful GPUs at scale for a low price, Colab needs to maintain the flexibility to adjust usage limits and hardware availability dynamically.

In the version of Colab that is free of charge, access to expensive resources like GPUs is heavily restricted. For the paid version of Colab, we target giving our users high value per their spend.

You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches.

What are the usage limits of Colab?

Colab is able to provide resources free of charge in part by having dynamic usage limits that sometimes fluctuate, and by not providing guaranteed or unlimited resources. This means that overall usage limits as well as idle timeout periods, maximum VM lifetime, GPU types available, and other factors vary over time. Colab does not publish these limits, in part because they can vary over time.

You can access more compute power and longer runtimes by purchasing one of our paid plans here. These plans have similar dynamics in that resource availability may change over time. Paid users whose compute unit balance is exhausted will revert to the free-of-charge tier policies and restrictions until the balance is increased.

You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches.

What types of GPUs are available in Colab?

The types of GPUs that are available in Colab vary over time. This is necessary for Colab to be able to provide access to these resources free of charge.

You can access premium GPUs subject to availability by purchasing one of our paid plans here.

If you would like access to specific dedicated hardware, explore using GCP Marketplace Colab.

How long can notebooks run in Colab?

Colab prioritizes interactive compute. Runtimes will time out if you are idle.

In the version of Colab that is free of charge notebooks can run for at most 12 hours, depending on availability and your usage patterns. Colab Pro, Pro+, and Pay As You Go offer you increased compute availability based on your compute unit balance.

In general, notebooks can run for at most 12 hours, depending on availability and your usage patterns. You can expect to experience backend termination if you exhaust your available compute units on a Pro, Pro+, or Pay As You Go plan.

Colab Pro+ supports continuous code execution for up to 24 hours if you have sufficient compute units. Idle timeouts only apply if code execution terminates.

You can fully relax any runtime limits and idle timeouts by purchasing a dedicated VM at GCP Marketplace.

How much memory is available in Colab?

In the version of Colab that is free of charge you are able to access VMs with a standard system memory profile.

In paid versions of Colab you are able to access machines with a high memory system profile subject to availability and your compute unit balance.

Note that memory refers to system memory. All GPU chips have the same memory profile.

How can I get the most out of Colab?

Consider closing your Colab tabs when you are done with your work, and avoid opting for GPUs or extra memory when it is not needed for your work. This will make it less likely that you will run into usage limits within Colab. You can always purchase more compute via Pay As You Go should you hit limits.

For more information on getting the most out of the paid version of Colab, see Making the Most of your Colab Subscription.

I saw a message saying my GPU is not being utilized. What should I do?

Colab offers optional accelerated compute environments, including GPU and TPU. Executing code in a GPU or TPU runtime does not automatically mean that the GPU or TPU is being utilized. To avoid hitting your GPU usage limits, we recommend switching to a standard runtime if you are not utilizing the GPU. Choose Runtime > Change Runtime Type and set Hardware Accelerator to None.

For examples of how to utilize GPU and TPU runtimes in Colab, see the Tensorflow With GPU and TPUs In Colab example notebooks.

AI Coding

How do I get access to AI coding in Colab?

We are slowly rolling out AI coding features like AI-enabled autocompletions, natural language to code, and a chatbot based on Google's most advanced coding assistance models.

Paid subscribers in select locales have access to these features now.

Additionally, code generation is available for a limited time for unsubscribed users.

Sadly, we do not support Google Workspace accounts at this time. We're working on enabling the features for those account types soon.

Can I rely on AI coding features in Colab for production quality work?

Colab can help with coding and topics about coding, but AI coding in Colab is still experimental and you are responsible for your use of code or coding explanations. You should use discretion and carefully test and review all code for errors, bugs, and vulnerabilities before relying on it.

If any generated code is subject to an open source license, Colab will cite it.

What can I ask the Colab AI chatbot?

Please only use the Colab AI chatbot to ask questions related to Colab or coding in Colab. If you want to ask a chatbot about another subject, we recommend Bard for general queries (and questions about other languages like Java!)

What languages can Colab help me with?

AI coding in Colab works best and is optimized for Python.

Does Colab give accurate and safe responses?

AI coding in Colab is experimental and some of the responses may be inaccurate, so double-check Colab's responses. With your feedback, AI coding in Colab is getting better every day.

Accelerating people's ideas with generative AI is truly exciting, but it's still early days, and AI coding is an experiment. While Colab has built-in safety controls and clear mechanisms for feedback in line with our AI Principles, be aware that it may display inaccurate information, links or offensive statements.

How can I give feedback about a specific AI response?

If you get an AI response that you feel is unsafe, not helpful, inaccurate, or bad for any other reason, you can let us know by submitting feedback.

At the bottom right of the response, click the thumbs up or thumbs down icons.

How can I turn off AI coding in Colab?

If you wish to disable AI coding in Colab, from the Tools menu select Settings, then Colab AI.

In that space you'll be able to revoke consent and hide AI coding features.

How and when does Colab cite sources in its responses?

AI coding in Colab, like some other standalone LLM experiences, is intended to generate original content and not replicate existing content at length. We've designed our systems to limit the chances of this occurring, and we will continue to improve how these systems function. If Colab does directly quote at length from a source, it cites that source.

What data is collected? How is it used?

When you use generative AI features in Colab, Google collects prompts, related code, generated output, related feature usage information, and your feedback. Google uses this data to provide, improve, and develop Google products and services and machine learning technologies, including Google's enterprise products such as Google Cloud.

To help with quality and improve our products, human reviewers may read, annotate, and process your prompts, generated output, related feature usage information, and your feedback. Please do not include sensitive (e.g., confidential) or personal information that can be used to identify you or others in your prompts or feedback. Your data will be stored in a way where Google cannot tell who provided it and can no longer fulfill any deletion requests and will be retained for up to 18 months.

What is the difference between Generate in the code cell and the Colab AI chatbot?

Generate in the code cell provides in-context help to write code snippets for you. Code is generated using your prompt as well as nearby notebook content to provide context to the model.

The Colab AI chatbot can be used for more general questions about Python. It provides explanations along with code snippets.

Additional Questions

What browsers are supported?

Colab works with most major browsers, and is most thoroughly tested with the latest versions of Chrome, Firefox and Safari.

How is this related to colaboratory.jupyter.org?

In 2014 we worked with the Jupyter development team to release an early version of the tool. Since then Colab has continued to evolve, guided by internal usage.

What about other programming languages?

Colab focuses on supporting Python and its ecosystem of third-party tools. We're aware that users are interested in support for other Jupyter kernels (eg R or Scala). We would like to support these, but don't yet have any ETA.

I found a bug or have a question, who do I contact?

Open any Colab notebook. Then go to the Help menu and select ”Send feedback...”.

Why prompt to enable third-party cookies?

Colab uses HTML iframes and service workers hosted on separate origins in order to display rich outputs securely. Browsers require enabling third-party cookies to use the service workers within iframes. An alternative to enabling third-party cookies for all sites is to allow the following hostname in your browser settings: googleusercontent.com.

How do I change the editor font?

Colab uses a generic monospace font for the editor. You can configure what font family is used for monospace in most modern browsers. Here's a few common ones:

Does Colab support Python 2?

Python 2 is no longer supported in Colab. For information on migrating your code from Python 2 to Python 3, see Porting Python 2 Code to Python 3.

Where can I learn more about the paid versions of Colab?

There is an FAQ on the sign-up page.

How does billing work for the paid versions of Colab?

Information for Colab Pro, Pro+, and Pay As You Go, including pricing and how upgrades are handled, can be found at the sign-up page.

How do I access Colab with a Workspace account?

Access to Colab for Workspace users is controlled by the Workspace on/off control accessible to your organization's administrator.

Workspace for Education organizations are required to obtain parental consent for students' (under the age of 18) use of Additional Services with their Google Workspace for Education account. This can be achieved with this notice template. Please be sure to include Colab in the list of additional services.

For more information, please read our Help Center article “Communicating with Parents and Guardians about Google Workspace for Education”.