This product has charges associated with it for seller support. This VM offers a hassle-free setup with <b>Jupyter</b> for projects, <b>Jupyterhub</b> for multiuser collaboration, a <b>Jupyter AI extension</b> for for <b>LLM and Generative AI development</b>, and preloaded popular libraries like TensorFlow and PyTorch. It also comes with pre-configured <b>NVIDIA GPU drivers and CUDA libraries</b>.
%ai commands for LLM and Generative AI development
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JupyterLab
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Jupyter Console
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Add Multiple Users
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Important: For step by step guide on how to setup this vm , please refer to our Getting Started guide
If you are AI/ML practitioner or someone who is starting their AI/ML journey but do not want to spend hours setting up the right environment , this VM is for you. It includes :
Jupyter : Your AI/ML Playground
Jupyterhub: Making your AI/ML projects more collaborative by providing multi-user environment and enabling easy code and data sharing
3.Jupyter AI extension : your gateway to generative AI within Jupyter
Provides better data privacy and control as your data, models, code & other information is stored on the VM
Preinstalled popular AI/ML libraries such as TensorFlow, PyTorch, scikit-learn and many more
Pre-configured NVIDIA GPU drivers & CUDA libraries
The preinstalled Juputer and AI/ML libraries jump-start your AI/ML development by saving you hours of installation time.
Jupyterhub gives you the collaboration capabilities by allowing a multi-user environment within the same VM. This not only makes it easy to share the AI/ML work , but makes it more cost efficient in a team setup by allowing multiple users/team members to share the same VM infrastructure instead of each user creating their own VM/notebooks.
With the Jupyter AI extension, you can seamlessly integrate with 100+ widely used LLMs from 10+ model providers such as OpenAI for ChatGPT, Anthropic, Hugging Face, AI21, SageMaker to name a few. Complete list of supported LLM Model providers is available here.
The JupyterAI extension comes with built-in LLM Chat UI for seamless collaboration for generative AI. Enjoy flexibility with support for diverse models and providers, seek code suggestions, debugging tips, or even have code snippets generated for you by interacting with the chat UI.
In addition to the Chat UI, the JupyterAI extension comes with %ai and %%ai magic commands turning your Jupyter into a generative AI playground anywhere the IPython kernel runs!
The VM also has pre-configured NVIDIA GPU drivers & CUDA libraries saving you hours of driver setup and configuration hassle so you can harness the power of GPU resources for your AI/ML workload and conduct advanced data analysis with ease.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
You pay by the hour based on the AWS EC2 instance type you run. The software price is the same across instances; your cost changes with the compute you pick. Options span many families: general-purpose (t2, t3, m4, m5), compute-optimized (c3, c4, c5), memory-optimized (r3, r4, r5, x1), storage-optimized (i2, i3, d2, h1), and GPU-accelerated (g2, g3, g4dn, p2, p3, f1). Smaller instances suit light work; larger sizes and GPU families support heavier AI/ML tasks. GPU instances from the g4dn family add GPU acceleration. Billing runs only while an instance is active.
Top-of-mind questions for buyers
What resources come with the default instance if I don't change the type?
The instance defaults to the t2.large type, which provides 2 vCPUs and 8 GB RAM. You can change this before launch. For GPU-accelerated work, select an instance from the g4dn family on the configuration page. Your hourly cost reflects whichever instance type you pick.
Am I charged when the instance is stopped or not in use?
Hourly software charges apply only while the instance runs. A stopped instance stops accruing software charges. Note that underlying AWS storage fees may still apply to a stopped instance, but the per-hour software meter counts running time only.
Do I pay extra for the Jupyter AI chat feature and its language model connections?
No separate software charge applies for the built-in AI chat plugin; it comes with the VM. You pay only the hourly rate for your chosen instance type. To use external language models, you supply your own API keys from those model providers, which may carry their own separate costs.
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
jupyterhub upgraded to version 5.4.3 on host ubuntu 2404
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This product has charges associated with it for seller support. This VM offers a hassle-free setup with Jupyter for projects, Jupyterhub for multiuser collaboration, a Jupyter AI extension for for LLM and Generative AI development, and preloaded popular libraries like TensorFlow and PyTorch. It also comes with pre-configured NVIDIA GPU drivers and CUDA libraries.
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