Page 25 - Red Hat PR REPORT - OCTOBER 2025

Press Release

Red Hat Brings Distributed AI Inference to Production AI Workloads

with Red Hat AI 3

Red Hat’s hybrid cloud-native AI platform streamlines AI workflows and offers powerful new inference
capabilities, building the foundation for agentic AI at scale and empowering IT teams and AI engineers to
innovate faster and more efficiently

October 15, 2025 – Red Hat, the world's leading provider of open-source solutions, today announced Red
Hat AI 3, a significant evolution of its enterprise AI platform. Bringing together the latest innovations of
Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) and Red Hat OpenShift AI, the platform
helps simplify the complexities of high-performance AI inference at scale, enabling organizations to more
readily move workloads from proofs-of-concept to production and improve collaboration around AI-
enabled applications.

As enterprises move beyond AI experimentation, they face significant hurdles, including data privacy, cost
control and managing diverse models. “The GenAI Divide: State of AI in Business” from the Massachusetts
Institute of Technology NANDA project, highlights the reality of production AI, with approximately 95% of
organizations failing to see measurable financial returns from ~$40 billion in enterprise spending.

Red Hat AI 3 focuses on directly addressing these challenges by providing a more consistent, unified
experience for CIOs and IT leaders to maximize their investments accelerated computing technologies. It
makes it possible to rapidly scale and distribute AI workloads across hybrid, multi-vendor environments
while simultaneously improving cross-team collaboration on next-generation AI workloads like agents, all
on the same common platform. With a foundation built on open standards, Red Hat AI 3 meets
organizations where they are on their AI journey, supporting any model on any hardware accelerator,
from datacentres to public cloud and sovereign AI environments to the farthest edge.

From training to "doing": The shift to enterprise AI inference

As organizations move AI initiatives into production, the emphasis shifts from training and tuning models
to inference, the “doing” phase of enterprise AI. Red Hat AI 3 emphasizes scalable and cost-effective in-
ference, by building on the wildly-successful vLLM and llm-d community projects and Red Hat’s model
optimization capabilities to deliver production-grade serving of large language models (LLMs).

To help CIOs get the most out of their high-value hardware acceleration, Red Hat OpenShift AI 3.0
introduces the general availability of llm-d, which reimagines how LLMs run natively on Kuber-
netes. llm-d enables intelligent distributed inference, tapping the proven value of Kubernetes or-
chestration and the performance of vLLM, combined with key open source technologies like Kuber-