AI Notebooks - Features, Capabilities and Limitations
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27.01.2026 
Cloud / AI Notebooks
AI Notebooks is covered by OVHcloud Public Cloud Special Conditions.
Objective
This page provides the technical features, capabilities and limitations of the Public Cloud AI Notebooks offer.
Features
Available features
AI Notebooks are Managed Jupyter or VS Code notebooks, linked to compute resources (CPUs, GPUs) and storage. You can compare them to Google Colab or Amazon Sagemaker notebooks.
| Feature | Details |
|---|---|
| Live code editor and AI environments | |
| Jupyter and VS Code | You can use Jupyter or VS Code as your preferred live-code editor. If you opt for VS Code, you can also set up a remote connection (for example, from your laptop). |
| Preinstalled Machine Learning environments | AI Notebooks comes with a generic Python environment (Conda) or pre-installed ones, such as Pytorch, Tensorflow, HuggingFace and more |
| Easy customization | AI Notebooks allows installation of almost any Conda or Pip packages. You can easily customize your environment to suit your needs. |
| Management | |
| Multiple ways to manage your notebooks | You can manage your AI Notebooks through the OVHcloud Control Panel, CLI, API or Python SDK. Depending on your needs, you can easily automate their creation and deletion as well. |
| Easy start and Stop | You can start and stop a notebook in one click. Once stopped, your notebook environment is kept and you can restart it later, without losing your data and experiments. |
| Compute resources | |
| Guaranteed compute resources | Select the amount of CPUs or GPUs required during the creation of the AI Notebooks. Once launched, you will keep these resources as long as your notebook is running. |
| Background execution | Your tasks can be executed in the background, meaning that closing your Web browser will have no effect on your work. |
| No maximum runtime | Your tasks can last as long as your notebook is running. |
| Monitoring tools | Each AI Notebooks service comes with a native Grafana dashboard, allowing you to keep track and monitor your CPU, GPU, RAM and storage resources. |
| Storage | |
| Fast and flexible storage | Each AI Notebooks service comes with local storage, but also the ability to attach remote storage from Object Storage. From a few GiB to multiple TiB, we push your data near our compute power on fast SSD storage for better performances. |
| Git repositories importation | During the creation of your AI Notebooks, you can specify one or multiple Git repositories to download inside your notebook environment. |
| Security | |
| Open or restricted authentication | During the creation of your AI Notebooks, select open or restricted access to your notebook. If restricted, people can be granted access via token or credentials to securely access your environment. |
| European values | We respect your privacy and will never use your personal data for our internal purposes. |
| Availability and billing | |
| Easy billing | You only pay for what you consume, billed per minute. |
| Available in many countries | AI Notebooks requires an OVHcloud account. We currently accept dozens of countries. Once created, you will have access to the whole set of features. |
Command line interface (CLI)
AI Notebooks is compliant with the OVHcloud AI CLI. Discover how to install the OVHcloud AI CLI.
Monitoring tools
To see information of your notebook, you can do so with the ovhai CLI using the command above:
You can then access your metrics through the Monitoring Url.
You are also able to check it from the OVHcloud Control Panel in your notebook's general information by clicking the Go to Graph Dashboard button.
Planned features
We continuously improve our offers. You can follow, vote and submit ideas to add to our roadmap at https://github.com/ovh/public-cloud-roadmap/projects/4.
Capabilities and limitations
Supported regions for notebooks
AI Notebooks can be used from any country in the world, as long as you have an OVHcloud account. Physically, two datacenters are available:
BHS(Beauharnois, Canada, America)GRA(Gravelines, France, Europe)
Attached resources
Compute resources
You can either choose the number of GPUs or CPUs for a notebook, not both.
By default, a notebook uses one GPU.
The memory resource is not customizable.
If you choose GPU:
- CPU, memory and local storage resources are not customizable but scaled linearly with each additional GPU.
If you choose CPU:
- Memory and local storage resources are not customizable but scaled linearly with each additional CPU.
The maximum amount of CPU/GPU, memory per CPU/GPU and local storage is available on the OVHcloud website, Control Panel and the ovhai CLI.
For your information, the current limits are:
- CPU: 12 per notebook.
- GPU: 4 per notebook.
Available hardware for AI Notebooks
Currently, we provide:
- NVIDIA H100
- NVIDIA Ampere A100
- NVIDIA Ampere A10
- NVIDIA Tesla V100S
- NVIDIA L4
- NVIDIA L40s
- Intel CPU vCores
Pricing is available here.
Available storage
Local storage
Each AI Notebooks comes with a local storage space, which is ephemeral. When you delete your notebook, this storage space is also deleted. This storage space depends on the selected instances during the notebook creation. Please refer to the compute resources section for more information.
Local storage is limited and not the recommended way to handle data, see the OVHcloud documentation on data for more information.
Attached storage
When attaching data volumes to your AI Notebooks, you can use storage from Public Cloud Object Storage. This allows you to work with large datasets, while ensuring persistence even if you delete your notebooks.
Ensure that the Object Storage bucket is located in the same region as your AI Notebook.
Your Public Cloud Project can store unlimited data in Object Storage buckets. However, when you mount an Object Storage bucket as a volume, there is a usage limit of 10 TB per Public Cloud Project. This limit applies to the total storage consumed by all volumes attached simultaneously across your AI Notebooks, AI Training jobs, and AI Deploy apps.
When the same volume is used across multiple resources, enabling caching allows shared access to the volume data, preventing multiple copies from consuming additional storage quota. Without caching, each instance will maintain a separate copy of the volume data, increasing the total storage usage linearly.
Maximum execution time
There is no duration limitation on AI Notebooks execution.
However, by default, your AI Notebook will automatically shut down after 7 consecutive days of being in a RUNNING state. All your settings and data are preserved and you can start it again anytime. You can also enable Automatic Restart to have it restart every 7 days, or contact our support to extend this period to 28 days.
Live-code editors
You can choose between two live-code editors to launch and edit your notebook:
- Jupyterlab
- VS Code
You cannot install your own code editor on AI Notebooks.
With VS Code, you get the capability to use remote connections (from a local computer).
Pre-installed AI environments
OVHcloud AI Notebooks comes with pre-installed AI environments.
List of available AI Environments:
- HuggingFace Transformers
- Miniconda (Python generic)
- Miniconda with Colab Compatibility
- MLR3 (collection of R Packages)
- PyTorch
- Scikit-Learn
- TensorFlow
Environment customization
Each environment can be customized directly with PIP or CONDA (we support almost any package and library).
Limitations:
-
You are not administrator (root). You cannot install linux packages (such as apt-get).
-
AI Notebooks does not allow the use of custom Docker images. In case you need a very specific package or framework, you can bring your custom Docker images with OVHcloud AI Training.
AI Training allows you to benefit from the same technology and pricing, but you can create notebooks directly with your own Docker images. If you want to build and use a custom Docker image, you can do it with AI Training by following this tutorial.
Network
-
Public networking can be used for all the AI Tools.
-
Private networking (OVHcloud vRack) is not supported.
Available ports to public network
Each notebook exposes a public URL that defaults to port 8080. This default port cannot be changed.
This public URL starts with the notebook's ID (filled with 0 here) and looks like the following:
- https://00000000-0000-0000-0000-000000000000.notebook.gra.ai.cloud.ovh.net
However, you can access other ports than the default 8080 by appending its number to your notebook URL. For example, if you want to access port 8501 from your notebook, you will have to add -8501 to your notebook URL. Your notebook URL for accessing the 8501 port will then be https://00000000-0000-0000-0000-000000000000-8501.job.gra.ai.cloud.ovh.net/
Only the HTTP layer is accessible.
Quotas per Public Cloud project
Each Public Cloud project grants a customer by default a maximum of 4 GPUs used simultaneously. Reach out to our support if you need to increase this limitation.
Go further
Browse the full AI Notebooks documentation to further understand the main concepts and get started.
If you need training or technical assistance to implement our solutions, contact your sales representative or click on this link to get a quote and ask our Professional Services experts for a custom analysis of your project.
Feedback
We would love to help answer questions and appreciate any feedback you may have.
Are you on Discord? Connect to our channel and interact directly with the team that builds our AI services!
AI Notebooks - Billing and lifecycle
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