Sold by: Red Hat
Deployed on AWS
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.
4.5
Overview
Red Hat AI Enterprise is an integrated AI platform that provides the foundation for building, developing, and deploying AI-powered applications across the hybrid cloud. By unifying the model and AI application lifecycles, it ensures consistent security, governance, and management to minimize operational complexity and risk. Powered by Red Hat OpenShift, the platform unifies the entire lifecycle - from development and tuning to high-performance inference, onto a centralized infrastructure. It addresses modern AI use cases, including predictive, generative, and agentic AI, by providing tools like optimized vLLM runtimes for high-performance inference and the Llama Stack for agentic workflows.
Key benefits include:
- Accelerated Time-to-Value:: Application life-cycle management and policy management across multiple Kubernetes clusters.
- Increased Operational Efficiency: Streamlines workflows and uses intelligent resource allocation to maximize the value of infrastructure like GPUs.
- Mitigated Risk: Provides a tested and supported AI stack that helps organizations meet data residency, sovereignty, and regulatory requirements.
Red Hat AI Enterprise transforms AI from a disjointed effort into a scalable, repeatable "factory" process.
Highlights
- AI lifecycle management: Manage the end-to-end process - from training and fine-tuning to serving and monitoring - for predictive, generative, and agentic AI on a single platform.
- High-performance inference at scale: The platform uses optimized runtimes like vLLM and the llm-d framework to deliver high-throughput, low-latency model serving. It also includes resource optimization capabilities to ensure efficient GPU utilization for both model training and inference.
- Unified enterprise platform experience: build and scale modern, AI applications on a single, centralized platform Kubernetes infrastructure powered by Red Hat OpenShift at its core through a consistent experience, anywhere, using familiar tools and frameworks. The platform includes a layered approach to security throughout the entire AI lifecycle.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Rhel 9.4
Deployed on AWS
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Financing for AWS Marketplace purchases
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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 |
|---|---|
p5en.48xlarge Recommended | $5.94 |
p6-b200.48xlarge | $5.94 |
p5.48xlarge | $5.94 |
p4d.24xlarge | $5.94 |
Dimensions summary
You pay by the hour based on the GPU-accelerated compute instance you run this platform on. Each dimension maps to a distinct instance type: p5en.48xlarge, p6-b200.48xlarge, p5.48xlarge, and p4d.24xlarge. These are not feature tiers. The platform capabilities stay the same across all four options. Your cost scales with the instance you choose and how many hours you run it. Pricing follows accelerator hardware, in line with the vendor's per-accelerator model, so heavier compute needs mean higher hourly charges.
Top-of-mind questions for buyers
Each dimension maps to a GPU-accelerated compute instance you run the platform on. The p5en.48xlarge, p6-b200.48xlarge, p5.48xlarge, and p4d.24xlarge names refer to instance types with different accelerator hardware. You pay for the instance you select, billed per hour of use.
Hourly software charges accrue only while an instance runs. Fully stopped instances stop the hourly meter. Underlying AWS storage or reserved-capacity fees may still apply separately, but the software license meters running time. Your cost scales with how many hours each instance runs.
Your bill follows the accelerator hardware of the instance you choose, in line with the vendor's per-accelerator model. Heavier compute instances carry higher hourly rates. You are billed for one instance type at a time, multiplied by the hours you run it. Platform capabilities stay the same across all four.
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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.
Additional details
Usage instructions
IMPORTANT: This marketplace listing is not meant for direct consumption by deploying a single virtual machine. Please follow the instructions in the official Red Hat AI Enterprise installation documentation. DO NOT create a Virtual Machine from this offering directly. Red Hat AI Enterprise (RHAIE) is supported only as an integrated, standalone AI platform. The RHAIE marketplace image is designed to automatically enable integrated pay-per-use or subscription billing for your full cluster environment, which bundles Red Hat OpenShift, Red Hat OpenShift AI, and full hardware accelerator entitlements. There are two general ways this marketplace image is utilized during a Red Hat AI Enterprise deployment:
Installer-provisioned infrastructure: If you install your cluster on infrastructure that the installation program provisions, you must specify this marketplace image details (publisher, offer, and SKU) directly inside your install-config.yaml configuration file before initiating the deployment. User-provisioned or existing infrastructure: If you manage your own infrastructure or are adding dedicated GPU compute nodes to an existing cluster, you must update your OpenShift MachineSet configurations to target this specific marketplace image to ensure proper workload execution and billing synchronization. For more information and detailed step-by-step cluster deployment workflows, please see the official Red Hat AI Enterprise installation guide.
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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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The listing is a subscription for Red Hat Ansible Automation Platform. It is subscription only and and is meant to be used with an instance of Ansible deployed on your AWS infrastructure following the standard guide for deploying Ansible following sizing guidelines. It can also be installed with an operator on Red Hat OpenShift on AWS (ROSA), or on OpenShift running directly on AWS infrastructure.
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Customer reviews
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.
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.
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 easy to customize and it runs almost anywhere, that is , I can run it on AWS,G Cloud, Azure or even in my laptop.
Also data privacy is 100% in our control, since all the data are saved in our own server.
The most lovable thing about RHEL AI is easy to customize and it runs almost anywhere, that is , I can run it on AWS,G Cloud, Azure or even in my laptop.
Also data privacy is 100% in our control, since all the data are saved in 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.
Filip D.
Enterprise-Ready Linux for AI Experiments with Strong Red Hat Integration
Reviewed on Aug 20, 2026
Review provided by G2
What do you like best about the product?
More than solid and enterprise-ready environment for working with AI models as we experiment a lot in an AI world. Linux generally is a stable, flexible and most reliable OS. We appreciate a strong integration with the broader Red Hat system. The value is more than good to what we're paying, especially the enterprise-grade security, stability and support which Red Hat provides more than good I'd say.
What do you dislike about the product?
Can feel a bit more complex using it the first time, especially if you're new to Red Hat ecosystem or Linux generally.
What problems is the product solving and how is that benefiting you?
It helps us to create I would say more consistent and manageable environment for developing, testing and running these AI workloads.
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