Red Hat AI Inference Server

Explore how Red Hat OpenShift AI uses LLM-generated summaries to distill product reviews into a form users can quickly process.

Learn how to build AI-enabled applications for product recommendations, semantic product search, and automated product review summarization with OpenShift AI.

Deploy an Oracle SQLcl MCP server on an OpenShift cluster and use it with the OpenShift AI platform in this AI quickstart.

Explore the latest release of LLM Compressor, featuring attention quantization, MXFP4 support, AutoRound quantization modifier, and more.

This article compares the performance of llm-d, Red Hat's distributed LLM inference solution, with a traditional deployment of vLLM using naive load balancing.

Whether you're just getting started with artificial intelligence or looking to deepen your knowledge, our hands-on tutorials will help you unlock the potential of AI while leveraging Red Hat's enterprise-grade solutions.

Take a look back at Red Hat Developer's most popular articles of 2025, covering AI coding practices, agentic systems, advanced Linux networking, and more.

Discover 2025's leading open models, including Kimi K2 and DeepSeek. Learn how these models are transforming AI applications and how you can start using them.

Run the latest Mistral Large 3 and Ministral 3 models on vLLM with Red Hat AI, providing day 0 access for immediate experimentation and deployment.

Use SDG Hub to generate high-quality synthetic data for your AI models. This guide provides a full, copy-pasteable Jupyter Notebook for practitioners.

Move larger models from code to production faster with an enterprise-grade