SYDNEY, AUSTRALIA – FEBRUARY 25, 2026 – Red Hat, the world’s leading provider of open source solutions, today announced Red Hat AI Enterprise, anintegrated AI platform for deploying and managing AI models, agents and applications across the hybrid cloud. It joins the Red Hat AI portfolio which includes Red Hat AI Inference Server, Red Hat OpenShift AI and Red Hat Enterprise Linux AI. Red Hat is also introducing Red Hat AI 3.3, bringing significant updates and enhancements across the company’s entire AI portfolio. Together, these solutions provide a comprehensive “metal-to-agent” stack, integrating the underlying Linux and Kubernetes infrastructure with advanced inference and agentic capabilities to help organisations move from fragmented experimentation to governed, autonomous operations.
The enterprise AI landscape is rapidly evolving from simple chat interfaces toward high-density, autonomous agentic workflows that require deeper integration across the entire technology stack. However, many organisations remain stuck in the “pilot phase” due to fragmented tools and inconsistent infrastructure. Red Hat AI Enterprise addresses this by unifying the model and application lifecycles allowing IT teams to manage AI as a standardised enterprise system rather than a siloed project – making AI delivery as reliable and repeatable as traditional enterprise software.
Red Hat AI Enterprise: The foundation for AI production
Red Hat AI Enterprise provides core capabilities, including high-performance AI inference, model tuning and customisation and agent deployment and management, with the flexibility to support any model and any hardware across any environment. Fuelled by Red Hat OpenShift – the industry’s leading hybrid cloud application platform powered by Kubernetes – at its core, Red Hat AI Enterprise delivers a highly scalable and more consistent experience with a stronger security footprint, anywhere, using familiar tools and frameworks. For NVIDIA AI infrastructure, NVIDIA and Red Hat co-engineered the newRed Hat AI Factory with NVIDIA, combining Red Hat AI Enterprise and NVIDIA AI Enterprise to help speed and scale production AI for enterprises.
Key benefits of Red Hat AI Enterprise include:
· Faster, more cost-effective and scalable AI inference using thevLLM inference engine andllm-d distributed inference framework for optimised generative AI model deployments across hybrid hardware environments.
· Integrated observability and lifecycle management to help drive AI lifecycle governance and mitigate risk with an integrated, tested and interoperable enterprise-ready AI stack.
· Flexibility across the hybrid cloud by empowering organisations to deploy and manage AI models, agents and applications with greater consistency wherever their business needs to run backed by trusted Red Hat platforms.
Extending strategic flexibility and full-stack efficiency with Red Hat AI 3.3
Red Hat’s strategy centres on bridging the gap between mission-critical stability and frontier innovation through a unified platform. The latest software release expands model choice, deepens full-stack optimisation for next-generation silicon and hardens operational consistency for frontier models.
New features and enhancements include:
· Expanded model ecosystem with validated, production-ready compressed versions of Mistral-Large-3, Nemotron-Nano and Apertus-8B-Instruct, available via the OpenShift AI Catalog. Additionally, the release enables deployment of state-of-the-art models like Ministral 3 and DeepSeek-V3.2 with sparse attention, while delivering multimodal enhancements including 3x Whisper speedup, geospatial support, improved EAGLE speculative decoding and enhanced tool calling for agentic workflows.
· Self-service access to AI models with a technology preview of Models-as-a-Service (MaaS). IT teams can provide self-service access to privately hosted models via an API gateway. This centralised approach ensures that AI is available on-demand for internal users, fostering a ready-to-go AI foundation that promotes private and scalable AI adoption within the enterprise.
· Expanded hardware support including a technology preview of generative AI support on CPUs, starting with Intel CPUs for more cost-effective small language model (SLM) inference. Additionally, the platform has expanded its hardware certification forNVIDIA’s Blackwell Ultraand support for AMD MI325X accelerators.
· Unified data-to-model lifecycle secured by the new Red Hat AI Python Index. This trusted repository delivers hardened, enterprise-grade versions of critical tools—including Docling, SDG Hub, and Training Hub—enabling teams to move from fragmented experimentation to repeatable, security-focused production pipelines.
· Comprehensive AI observability and safety with greater visibility into model health, performance and behaviour. This provides real-time telemetry across AI workloads, llm-d deployments and Models-as-a-Service (MaaS) cluster and model usage and is paired with a technology preview of integrated NeMo Guardrails, enabling developers to enforce operational safety and alignment across AI interactions.
· Provide on-demand access to GPUs resources by empowering organisations to deploy their own internal GPU-as-a-Service capabilities through intelligent orchestration and pooled hardware access with automatic checkpointing to save the state of long-running training jobs, preventing work loss and maintaining more predictable compute costs, even in highly dynamic or preemptible environments.
Supporting Quotes
Joe Fernandes, vice president and general manager, AI Business Unit, Red Hat
“For AI to deliver true business value, it must be operationalised as a core component of the enterprise software stack, not as a standalone silo. Red Hat AI Enterprise is designed to bridge the gap between infrastructure and innovation by providing a unified metal to agent platform. By integrating advanced tuning and agentic capabilities with the industry-leading foundation of Red Hat Enterprise Linux and Red Hat OpenShift, we are providing the complete stack – from the GPU-accelerated hardware to the models and agents that drive business logic. Additionally, with Red Hat AI 3.3 organisations can move beyond fragmented pilots to governed, repeatable and high-performance AI operations across the hybrid cloud.”
Additional Resources
Learn more about Red Hat AI Enterprise
Learn more about Red Hat AI Factory with NVIDIA
Join theMarch 3rd roadmap session for a deeper dive on Red Hat AI 3.3
Learn more about IBM Fusion for Red Hat AI (IBM blog)
Connect with Red Hat
Learn more aboutRed Hat
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About Red Hat
Red Hat is the open hybrid cloud technology leader, delivering a trusted, consistent and comprehensive foundation for transformative IT innovation and AI applications. Its portfolio of cloud, developer, AI, Linux, automation and application platform technologies enables any application, anywhere—from the datacentre to the edge. As the world’s leading provider of enterprise open source software solutions, Red Hat invests in open ecosystems and communities to solve tomorrow’s IT challenges. Collaborating with partners and customers, Red Hat helps them build, connect, automate, secure and manage their IT environments, supported by consulting services andaward-winning training and certification offerings.
Forward-Looking Statements
Except for the historical information and discussions contained herein, statements contained in this press release may constitute forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements are based on the company’s current assumptions regarding future business and financial performance. These statements involve a number of risks, uncertainties and other factors that could cause actual results to differ materially. Any forward-looking statement in this press release speaks only as of the date on which it is made. Except as required by law, the company assumes no obligation to update or revise any forward-looking statements.
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