Red Hat AI Inference Server

The value of an AI model depends on its ability to deliver inference that is fast, scalable, and cost efficient. Inference—the act of executing a model to produce outputs—is where AI delivers real business impact. However, inference workloads can be highly resource intensive, driving up infrastructure costs, particularly when large models are deployed at scale. Organizations also require the freedom to deploy inference where it best fits their needs, whether in data centers, public clouds, or edge environments, using their preferred hardware.

As part of the Red Hat AI portfolio, Red Hat AI Inference Server delivers consistent, high-performance, and cost-effective inference at scale. It enables organizations to run any generative AI model on a wide range of hardware accelerators—including NVIDIA, Intel, and AMD—across data center, cloud, and edge environments, providing the flexibility needed to meet diverse business requirements.

Red Hat AI Inference Server improves inference efficiency through model optimization capabilities, such as using LLM Compressor to reduce the size of both foundation and fine-tuned models. It also offers rapid access to a curated set of validated and optimized generative AI models that are ready for inference deployment.

The platform supports a broad ecosystem of accelerators and models and can be deployed on a variety of infrastructures and operating systems, including Red Hat AI platforms, Red Hat Enterprise Linux, Red Hat OpenShift, as well as non–Red Hat Linux or Kubernetes distributions. This flexibility allows organizations to align inference deployments with their existing architectures and operational strategies.