Accelerate your AI and hybrid cloud strategy with a secure, scalable and open platform built by IBM and Red Hat.
Scalable. AI-Ready. Open. Flexible.
AI-ready solutions from Red Hat and IBM Cloud
Red Hat® AI on IBM Cloud® provides a consistent and secure way to build, train, customize and deploy AI and machine learning workloads across hybrid cloud environments. The portfolio combines open source innovation with enterprise-grade cloud infrastructure, helping IT teams reduce operational complexity and accelerate AI adoption. This portfolio is designed for organizations that need reliable AI infrastructure and a faster path from prototype to production.
Customize models with your own enterprise data—then efficiently serve them in production with integrated model‑tuning, compression, and inference capabilities.
Deploy AI workloads on a consistent hybrid cloud platform, including high‑performance, scalable inference for real‑time and agentic applications.
Scale training and inference with GPU‑optimized infrastructure and distributed inference runtimes that maximize throughput and cost‑efficiency across diverse accelerators.
Apply security, governance and compliance across environments—from model creation through production inference—to ensure controlled and trustworthy AI operations.
Red Hat AI solutions on IBM Cloud
One open, hybrid, enterprise-grade AI platform.
- Red Hat AI Inference on IBM Cloud
- OpenShift AI on IBM Cloud
- Red Hat Enterprise Linux AI on IBM Cloud
- InstructLab on IBM Cloud
Deliver high performance, scalable AI inference anywhere
Red Hat® AI Inference provides a consistent, high‑performance platform to run generative AI models across hybrid cloud environments. Built on Red Hat OpenShift AI and powered by vLLM and llm‑d, it enables fast, predictable, and cost‑efficient inference for real‑time and agentic workloads.
Key capabilities
- Any‑model, any‑accelerator deployment across hybrid cloud
- Distributed inference for low‑latency, high‑throughput production serving
- Model optimization and compression to reduce cost per token
- GenAI‑specific telemetry for performance, reliability and SLA tracking
- Enterprise‑grade governance, security and observability
Red Hat AI Inference provides a scalable, governed foundation for delivering production‑ready inference across teams, applications, and environments.
Build, deploy and manage AI applications at scale
OpenShift AI on IBM Cloud brings Red Hat® OpenShift® together with integrated MLOps and generative AI tools. It gives you a consistent, Kubernetes-based platform to manage AI workloads across hybrid cloud environments.
Key capabilities:
Optimized infrastructure for AI training and inference
Integrated pipelines for end‑to‑end model lifecycle management
GPU‑enabled compute options with intelligent autoscaling
Enterprise‑grade security, compliance and observability
Unified support delivered jointly by IBM and Red Hat
OpenShift AI provides a reliable and secure foundation for AI operations and production deployment.
A secure, high-performance operating system for AI workloads
Red Hat Enterprise Linux AI (RHEL AI) offers a stable environment to run and customize LLMs across cloud, data center and edge locations. It includes the open source Granite® model family and InstructLab tools, giving teams a ready-to-use AI development and deployment environment.
Key capabilities:
- Enterprise security and lifecycle management
- Optimized support for GPUs and AI accelerators
- Portable deployments across hybrid cloud
- Consistent operations aligned with standard RHEL processes
RHEL AI provides a secure and predictable foundation for enterprise AI workloads.
Customize enterprise AI models with a managed service
Red Hat AI InstructLab™ on IBM Cloud is a fully managed service —offered as a feature of Red Hat AI Inference on IBM Cloud— that enables you to customize large language models without requiring full retraining. It uses synthetic instruction generation to add new behaviors, skills and domain knowledge, helping reduce GPU costs and speed up model development.
Key InstructLab capabilities:
- Model customization with enterprise data
- Lower infrastructure requirements than traditional fine‑tuning
- Secure IBM Cloud environment for data protection
- Standardized workflows across teams
InstructLab provides a faster way to build AI models that fit your business needs and governance requirements.
Why Red Hat AI on IBM Cloud
Red Hat AI on IBM Cloud provides a secure, consistent and scalable foundation to move AI workloads from pilot to production across your hybrid cloud.
Move from pilot to production faster with streamlined tools, automated workflows, and ready‑to‑run high‑performance inference.
Run any model on any supported accelerator with a unified experience across on‑premises and cloud environments.
Protect sensitive workloads with built‑in governance, access controls, auditability, and secure inference operations.
GPU‑optimized compute, storage and networking deliver the performance needed for training and inference at scale.
High‑quality data, validated models and robust deployment options help improve system accuracy and decision-making.
Optimize resource usage and reduce cost per token with intelligent batching, model compression, and efficient accelerator utilization.
Security and privacy controls help to support regulatory needs.
A complete stack—from infrastructure to model lifecycle and production inference—reduces complexity and speeds enterprise adoption.
Case studies
Born digital AI platforms for exponential digital revenue streams.
Generative AI further enhances a world-class digital experience.
Transforming collaboration across client-facing teams at IBM.
Acing the US Open digital experience.
Related products
Bring mission‑critical applications to market faster with a secure, managed Red Hat OpenShift offering.
Comprehensive suite of products and services designed to accelerate the development and deployment of AI, orchestration and virtualization solutions across hybrid cloud environments.
Accelerators on IBM Cloud. The power of choice for your AI deployments.
AI‑first enterprises can reduce costs by using small, customized models to drive growth.