Sold by: Elm Computing
Deployed on AWS
Free Trial
AWS Free Tier
This product has charges associated with it for seller support.
Overview
This is a repackaged open source software product wherein additional charges apply for support by Elm Computing.
Disclaimer: All trademarks referenced in this listing belong to their respective owners. Their use does not imply any affiliation with or endorsement by the trademark holders.
Key Features:
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Multi-User Jupyter Notebooks: Purpose-built to host and serve Jupyter Notebooks for multiple users seamlessly.
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Comprehensive Python Environment: Comes preinstalled with hundreds of Python packages, offering a complete and ready-to-use environment for data science, machine learning, and more.
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PyTorch with GPU Support: Optimized for deep learning workflows, featuring PyTorch with full GPU acceleration capabilities.
For detailed documentation and additional information, visit: docs.elmcomputing.io
Highlights
- Up-to-date PyTorch
- GPU Support
- Elm Computing Support
Details
Sold by
Categories
Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
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.
Dimension | Cost/hour |
|---|---|
t3.xlarge Recommended | $0.10 |
t3.micro | $0.10 |
t3.large | $0.10 |
m7a.medium | $0.10 |
m5.16xlarge | $0.10 |
t3a.xlarge | $0.10 |
t3a.large | $0.10 |
m5.2xlarge | $0.10 |
g5.16xlarge | $0.10 |
t3a.2xlarge | $0.10 |
Dimensions summary
You pay by the hour for the software, and the rate depends on the AWS instance type you run it on. Each dimension maps to a specific EC2 instance size. General-purpose families (t3, t3a, m5, m5a, m6a, m7a and related variants) scale from small nano and micro sizes up to large metal instances. Compute-focused c5 families suit heavier processing needs. The g5 family adds GPU capacity for machine learning work. Larger instances carry higher hourly rates. You are billed only for the hours you run, with no upfront commitment.
Top-of-mind questions for buyers
Each hour covers the repackaged open-source JupyterHub software plus support from Elm Computing. The listing bundles Python packages, GPU support, and PyTorch on a hardened server. You run one EC2 instance of the chosen type, and the software rate is billed per running hour alongside AWS infrastructure charges.
The software rate meters running time only. When you stop the instance, no software hours accrue. You may still pay underlying AWS storage fees for the stopped volume, but that is separate from the per-hour software charge shown in the table.
The g5 family dimensions add GPU hardware suited to machine learning and PyTorch workloads. General-purpose (t3, t3a, m5, m6a, m7a) and compute-focused (c5) dimensions provide CPU-only capacity. Choose a g5 dimension when your work needs GPU acceleration; otherwise a CPU family may fit.
docs.elmcomputing.io
Helpful?
Vendor refund policy
Refunds are generally not available. Instances are billed hourly based on actual usage and can be terminated at any time to stop charges.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
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
Upgraded PyTorch to 2.8.0.0
Additional details
Usage instructions
Once the instance is started, you can access the JupyterHub server using its public IP address. For example, if the IP address is 10.11.12.13, entering http://10.11.12.13 in your browser will take you to the JupyterHub startup page.
When the JupyterHub server is first activated, a default user account, "jhub-admin", is automatically created.
Upon your first visit to the server, you will be prompted to set a password for "jhub-admin" on the signup page.
Unlike regular users, "jhub-admin" is immediately authorized to log in once the password is set.
For newly created users, an additional authorization step is required. This can be completed at: http://10.11.12.13/hub/authorize
If you need to update the password, you can do so at: http://10.11.12.13/hub/change-password
For detailed instructions, refer to the documentation at: https://docs.elmcomputing.io/ami/x86/pytorch/overview.html
Support
Vendor support
Please contact us at support@elmcomputing.io if any assistance is needed.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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