This product has charges associated with it for seller support. This image comes with a prebuilt Ubuntu 26.04 AMI for private local LLM experimentation on EC2 with Ollama, Open WebUI, and a small preloaded validation model.
This prebuilt AMI provides a ready-to-run local LLM environment on AWS EC2. It
combines Ollama for local model serving and Open WebUI for a browser interface to the Ollama backend.
Open Source Disclaimer
This is a repackaged open source software product wherein additional charges apply for support by Elm Computing.
Open source components included in this image remain subject to their respective
upstream licenses. Elm Computing provides packaging, configuration, documentation, maintenance, and support for this AMI; it does not claim ownership of upstream open source projects included in the image.
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.
What Is Included
Ollama local model server.
Open WebUI browser interface.
Preloaded smollm2:135m model for immediate validation.
Typical Use Cases
Evaluate local LLM workflows without wiring external model APIs.
Run a private Ollama endpoint inside an AWS account.
Provide a simple web UI for users testing Ollama-hosted models.
Notes
The included model is intentionally small. Pull larger Ollama models after
launch if your instance type has enough memory, CPU, and disk capacity.
Ollama uses CPU inference by default in this image.
Open WebUI listens on port 8080.
Ollama listens locally on port 11434; keep it local and use SSH tunneling
for direct API access.
For production deployments, configure secrets, access controls, and security
groups according to your organization's requirements.
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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.
Ollama with Open WebUI with support by Elm Computing
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. Each dimension maps to one instance size, so the software fee scales with the compute capacity you choose. Smaller instances like t3.nano or m5.large cost less per hour, while large and bare-metal instances like c8i.metal-96xl cost more. This hourly charge covers vendor support for the packaged open-source software; your AWS infrastructure is billed separately by AWS. There are no upfront commitments, so you pay only for the hours each instance runs.
Top-of-mind questions for buyers
What does the hourly software charge cover, and what is billed separately?
The hourly rate pays for vendor support of the packaged open-source software from Elm Computing. The listing repackages open-source products with support added on top. Your AWS compute, storage, and network usage for the chosen instance are billed separately by AWS at standard rates.
Am I charged the hourly software fee when my instance is stopped?
The software fee meters running instance-hours only. When you stop an instance, the hourly software charge stops accruing. Stopped instances may still incur AWS storage fees for attached volumes, but those come from AWS, not the software listing. You pay only for hours the instance actually runs.
Why does each dimension map to one instance type, and how do I pick one?
Each dimension corresponds to a single AWS EC2 instance size. You pick the instance whose CPU and memory match your workload. General-purpose (m, t), compute-optimized (c), and memory-optimized (r) families each suit different needs. Larger and bare-metal (.metal) sizes carry higher hourly rates because they provide more compute capacity.
docs.elmcomputing.io
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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.
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Legal
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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
Ollama and openwebui on Ubuntu 26.04
Additional details
Usage instructions
Browser Access
Use this path to open the web interface and start chatting with the preloaded model.
Launch
Launch an EC2 instance from the published AMI.
Choose t3.medium or larger for basic validation with the included smollm2:135m model. Larger models require larger instances and more disk capacity.
In the security group, allow Open WebUI only from trusted IP addresses.
Allow TCP port 8080 from your IP address or trusted network range.
Do not expose the Ollama API port 11434 publicly.
Open WebUI
After the instance is running, copy the EC2 instance public IPv4 address from the AWS console.
Open this URL in your browser:
URL: http://INSTANCE_PUBLIC_IP:8080
Replace INSTANCE_PUBLIC_IP with the EC2 instance public IPv4 address shown in the AWS console.
On first access, create the initial Open WebUI account. The image includes the small smollm2:135m model so you can validate chat immediately.
If the page does not load, confirm that the instance is running and that the security group allows TCP port 8080 from your current IP address.
Private Access And Administration
Use this section for command-line access, private access through SSH tunnels, direct Ollama API access, or additional model management.
SSH Access
Use the SSH command shown in the EC2 instance console. In the AWS console, select the instance, choose Connect, open the SSH client tab, and copy the generated command.
From an SSH session on the instance, use Ollama to pull additional models after launch.
Command: ollama pull llama3.2:1b
Command: ollama list
Choose model sizes that fit the instance memory and disk capacity. The root volume is intended for basic use and validation; increase storage before pulling larger models or maintaining multiple model copies. If model generation is slow, use a larger instance type or pull a smaller model. CPU inference speed depends heavily on instance size and model size.
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.
This product has charges associated with it for support. Ollama is a cutting-edge AI tool that empowers users to set up and run large language models, such as Llama 2 and 3, directly on their local machines. This innovative solution caters to a wide range of users, from experienced AI professionals to enthusiasts, enabling them to explore natural language processing without depending on cloud-based services.
This is a repackaged software product wherein additional charges apply for seller maintenance.
Deploy a powerful, self-hosted AI server supporting multiple LLMs (including Deepseek) via Open WebUI and Ollama. Streamline AI inference, customization, and local model management in a scalable AWS environment.
Deploy Open WebUI instantly with a preconfigured AMI for self hosted AI chat, LLM interaction, and collaborative AI workflows. This platform provides a modern web interface for large language models with secure access, customizable deployment, and scalable infrastructure for teams and developers.
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