Sold by: Red Hat Limited
Deployed on AWS
Red Hat® Enterprise Linux® AI is a foundation model platform to seamlessly develop, test, and run Granite family large language models (LLMs) for enterprise applications.
4.4
Overview
Red Hat Enterprise Linux AI is a foundation model platform for running LLMs in individual server environments. The solution includes the Red Hat AI Inference Server, which provides an immutable, purpose-built appliance optimized for inference. Packaging the OS and application together, Red Hat Enterprise Linux AI facilitates Day 1 operations to optimize model inference across the hybrid cloud. Its vLLM runtime maximizes throughput and minimizes latency. This is complemented by LLM compressor and Speculators for further model optimization and a pre-optimized model repository, ensuring fast and cost-effective deployments.
Highlights
- The Granite family of LLMs.
- A bootable image, including AI libraries such as PyTorch, and optimized inference for NVIDIA and enterprise-grade technical support.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Rhel 9.6
Deployed on AWS
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Pricing
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.
Dimension | Cost/hour |
|---|---|
p5.48xlarge Recommended | $0.40 |
p4d.24xlarge | $0.40 |
g6e.48xlarge | $0.40 |
Dimensions summary
You pay by the hour based on the GPU-accelerated compute instance you run. The three dimensions map to specific instance types: p5.48xlarge, p4d.24xlarge, and g6e.48xlarge. Each represents a different accelerator configuration, so your rate changes with the instance you select. Pricing scales with usage — you are billed for the hours each instance runs, with no upfront commitment. The license is priced per accelerator and includes all components needed to run large language models in a single server environment.
Top-of-mind questions for buyers
Each dimension maps to a specific GPU-accelerated instance type: p5.48xlarge, p4d.24xlarge, or g6e.48xlarge. You are billed per hour that instance runs. The license is priced per accelerator, so the number of accelerators in your chosen instance shapes your rate.
Hourly charges apply while an instance runs. When you stop or terminate the instance, the hourly software charge stops accruing. Underlying AWS storage or reserved resources may still bill separately, but the software license meters running hours only.
The instance type you select drives your rate. Each of the three dimensions carries a different accelerator configuration, so the p5.48xlarge, p4d.24xlarge, and g6e.48xlarge rates differ. You do not combine dimensions; you pick one instance and pay its hourly rate for the hours it runs.
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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
- Launch the product via 1-Click or the marketplace listing.
- Access your instance using ssh
- Open an SSH client
- Locate your private key file that was used to launch this instance. This file was downloaded when you created the key pair in AWS.
- Navigate to the directory where your .pem key file is located by using the command: cd path/to/your-key-file-directory.
- Set the permissions of your .pem file to ensure it is not publicly viewable by using the command: chmod 400 your-key-file.pem.
- Use the default username 'cloud-user' and the ssh key registered with AWS. Note that 'root' is disabled by default. Replace your-key-file.pem with your key file name and your-instance-public-dns with the public DNS or IP address of your instance.
Additional details
Usage instructions
Support
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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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Red Hat® Enterprise Linux® AI is a foundation model platform to seamlessly develop, test, and run Granite family large language models (LLMs) for enterprise applications.
Red Hat AI Enterprise is an integrated AI platform for deploying and managing efficient and cost-effective AI models, agents and AI-powered applications across hybrid cloud environments. It unifies AI model and application lifecycles to increase efficiency, accelerate delivery, and mitigate risk by providing a ready-to-use development environment with enterprise-grade capabilities. This platform is a tested, supported AI stack, powered by Red Hat OpenShift, that enhances interoperability and ensures business continuity. It includes core capabilities like model tuning, high-performance inference, agentic AI workflow management - with the flexibility to support any model, use any hardware, and deploy anywhere while meeting data location requirements.
Red Hat AI Enterprise is an integrated AI platform for deploying and managing efficient and cost-effective AI models, agents and AI-powered applications across hybrid cloud environments. It unifies AI model and application lifecycles to increase efficiency, accelerate delivery, and mitigate risk by providing a ready-to-use development environment with enterprise-grade capabilities. This platform is a tested, supported AI stack, powered by Red Hat OpenShift, that enhances interoperability and ensures business continuity. It includes core capabilities like model tuning, high-performance inference, agentic AI workflow management - with the flexibility to support any model, use any hardware, and deploy anywhere while meeting data location requirements.
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Customer reviews
Computer Software
Simple, Reliable Way to Use AI Tools Securely
Reviewed on Aug 28, 2026
Review provided by G2
What do you like best about the product?
It is very simple to manage and is reliable. It makes it easier to use AI tools in a secure manner.
What do you dislike about the product?
Troubleshooting issues can be difficult because there are many components involved, such as the model server, containers, and system resources.
What problems is the product solving and how is that benefiting you?
RHEL AI helps solve the problem of deploying and managing AI models in a secured and controlled environment. It helps me by providing a more consistent environment for testing, deploying and managing AI models, while giving better control over security and overall infrastructure.
Shashank s.
Enterprise-Ready Granite LLMs with Full Support and Legal Indemnification
Reviewed on Aug 25, 2026
Review provided by G2
What do you like best about the product?
One of the best parts I like about Red Hat is the Enterprise Granite models. RHEL AI includes access to the open source Granite family of LLMs developed by IBM Research. A major enterprise benefit is that these models are fully supported and legally indemnified by Red Hat.
What do you dislike about the product?
From what I’ve observed, one of the biggest selling points of RHELAI is the legal indemnification it offers. However, this protection only applies to the IBM Granite models. If I choose to run other open-source models, like Llama 3 or Mistral, on the platform, I lose that legal safety net, along with the specific enterprise support tied to the model itself. Even though it has a built in LLM compressor but running the Enterprise create generative AI requires serious hardware.
What problems is the product solving and how is that benefiting you?
For me, it’s an optimized, ready-to-use application that lowers the barrier to entry for Enterprise AI. It packages the operating system, AI models, and inference software together, so businesses can deploy AI without needing extensive data science expertise or having to deal with complex integration barriers. A few of the components and tools it provides are genuinely beneficial—for example, Red Hat AI inference, Enterprise granite models, bootable AI appliances, and the LLM compressor. When it comes to cost-effectiveness and efficiency, it generally improves GPU utilization and helps compress models. As a result, RHEL AI can significantly lower the compute cost and the cost per token associated with running generative AI.
Nazim Abdul Aziz S.
One of the best and easiest linux to use and learn.
Reviewed on Aug 24, 2026
Review provided by G2
What do you like best about the product?
The best thing about Red Hat Enterprise Linux AI, in my opinion, is its portability. It runs smoothly whether it’s deployed on a physical server or in the cloud. What I also like is the consistency—it’s built on the same foundation across different environments, so the experience remains familiar, reliable, and easy to manage. In my experience, Red Hat Enterprise Linux AI works well with other tools in the existing stack, especially Linux-based and enterprise tools. Since it follows the familiar Red Hat Linux foundation, integration and administration are relatively straightforward. However, depending on the use case, some additional configuration may be required when integrating it with newer AI or cloud-native tools.
What do you dislike about the product?
One of the biggest drawbacks of Red Hat Enterprise Linux AI is its cost. The pricing is quite high of this OS, especially when compared with the features and built-in tools. I also feel that it offers fewer built-in tools compared to Red Hat OpenShift AI, which makes OpenShift AI seem like a better value for more advanced AI workloads.
What problems is the product solving and how is that benefiting you?
It solves many day-to-day technical problems, especially in a corporate environment. One of its biggest advantages is that it’s built on a familiar Linux structure, which makes troubleshooting much easier. It also streamlines routine administration and feels more comfortable for users who already have Linux experience.
Jithin G.
Cost-Optimized, Customizable RHEL AI That Runs Anywhere
Reviewed on Aug 21, 2026
Review provided by G2
What do you like best about the product?
Comparing with other AI competitors, Red Hat Enterprise Linux AI is cost-optimized, especially when the user base is huge. The most lovable thing about RHEL AI is that it's easy to customize and it runs almost anywhere, whether on AWS, G Cloud, Azure, or even on my laptop. Also, data privacy is 100% in our control, since all the data is saved on our own server.
What do you dislike about the product?
RHEL AI has a very small community ecosystem, and learning about RHEL AI is tough compared to its competitors.
What problems is the product solving and how is that benefiting you?
We are using RHEL AI to integrate a real-time conversational chatbot. Before switching to RHEL AI, we relied on OpenAI, and because we have a huge user base with a large volume of active chats, the costs became extremely high. Integrating RHEL AI with our system took some time and effort, but once the integration was complete, our costs dropped significantly. The difference in billing is substantial, and this should save us a lot going forward.
Rinu L.
Red Hat Enterprise Linux AI: Secure, Reliable, and Enterprise-Ready AI Platform
Reviewed on Aug 12, 2026
Review provided by G2
What do you like best about the product?
Easy-to-use AI platform for enterprise workloads. It integrates well with Red Hat Enterprise Linux and supports secure AI/ML development as well as deployment.
Reliable performance for AI workloads and model development
Good value for the enterprise AI workloads and reduced infrastructure cost
Easy setup, clear documentation, and strong Red Hat support
Reliable performance for AI workloads and model development
Good value for the enterprise AI workloads and reduced infrastructure cost
Easy setup, clear documentation, and strong Red Hat support
What do you dislike about the product?
Initial setup can be complex
Higher learning curve for beginners
Enter pricing can be high
Require good Linux and AI knowledge
Some AI tools need extra configuration
Higher learning curve for beginners
Enter pricing can be high
Require good Linux and AI knowledge
Some AI tools need extra configuration
What problems is the product solving and how is that benefiting you?
Simplifies AI/ML development > faster development
Provides a secure AI environment > better data protection
Supports Enterprice AI workloads > reliable performance
Reduce infrastructure management > saves time
Integrates with existing Rd Hat environments > easier operations
Support AI model development and deployment > improves productivity
Provides a secure AI environment > better data protection
Supports Enterprice AI workloads > reliable performance
Reduce infrastructure management > saves time
Integrates with existing Rd Hat environments > easier operations
Support AI model development and deployment > improves productivity