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5/26/25, 11:40 AM Red Hat Unlocks Generative AI for Any Model and Any Accelerator Across the Hybrid Cloud with Red Hat AI Inference Server - Mi…
Red Hat Unlocks Generative AI for Any Model and
Any Accelerator Across the Hybrid Cloud with Red
Hat AI Inference Server
By PR News Desk 26/05/2025
Red Hat, the world’s leading provider of open source solutions, announced Red Hat AI Inference Server, a
significant step towards democratizing generative AI (gen AI) across the hybrid cloud. A new offering within
Red Hat AI, the enterprise-grade inference server is born from the powerful vLLM community project and
enhanced by Red Hat’s integration of Neural Magic technologies, offering greater speed, accelerator-
efficiency and cost-effectiveness to help deliver Red Hat’s vision of running any gen AI model on any AI
accelerator in any cloud environment. Whether deployed standalone or as an integrated component of Red
Hat Enterprise Linux AI (RHEL AI) and Red Hat OpenShift AI, this breakthrough platform empowers
organizations to more confidently deploy and scale gen AI in production.
Inference is the critical execution engine of AI, where pre-trained models translate data into real-world
impact. It’s the pivotal point of user interaction, demanding swift and accurate responses. As gen AI models
explode in complexity and production deployments scale, inference can become a significant bottleneck,
devouring hardware resources and threatening to cripple responsiveness and inflate operational costs.
Robust inference servers are no longer a luxury, but a necessity for unlocking the true potential of AI at
scale, navigating underlying complexities with greater ease.
Red Hat directly addresses these challenges with Red Hat AI Inference Server — an open inference solution
engineered for high performance and equipped with leading model compression and optimization tools. This
innovation empowers organizations to fully tap into the transformative power of gen AI by delivering
dramatically more responsive user experiences and unparalleled freedom in their choice of AI accelerators,
models and IT environments.
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