Red Hat AI Inference 3.4

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Release notes

Highlights of what is new and what has changed with this Red Hat AI Inference release

Getting started

Getting started with Red Hat AI Inference

Distributed Inference with llm-d

Architecture, components, and deployment of Distributed Inference with llm-d for scalable LLM serving on Kubernetes

Plan

Deploying Red Hat AI Inference in OpenShift Container Platform

Deploy Red Hat AI Inference in OpenShift Container Platform clusters that have supported AI accelerators installed

Deploying Red Hat AI Inference in a disconnected environment

Deploy Red Hat AI Inference in a disconnected environment using OpenShift Container Platform and a disconnected mirror image registry

Supported product and hardware configurations

Supported product and hardware configurations for deploying Red Hat AI software

Validated models

Red Hat AI validated models

Inference Operations

Inference serving language models in OCI-compliant model containers

Inferencing OCI-compliant models in Red Hat AI Inference

Speculative decoding

Speculative decoding with Red Hat AI Inference

Inference serving Mistral 3 models

Inference serving Mistral 3 models with Red Hat AI Inference

Inference serving geospatial foundation models

Inference serving geospatial foundation models with Red Hat AI Inference

Red Hat AI Model Optimization Toolkit

Compressing large language models with the LLM Compressor library

vLLM server arguments

Server arguments for running Red Hat AI Inference

Extending Red Hat AI Inference with tool calling capabilities

Configuring tool calling and chat templates for AI Inference

Additional Resources

Red Hat AI Inference Server 3.3

Switch to the Red Hat AI Inference Server 3.3 documentation

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