Red Hat AI     Build AI for your world

The Red Hat AI repository on Hugging Face is an open-source initiative backed by deep collaboration between IBM and Red Hat’s research, engineering, and business units. We’re committed to making AI more accessible, efficient, and community-driven from research to production.

We believe the future of AI is open. That’s why we’re sharing our latest models and research on Hugging Face, which are freely available to help researchers, developers, and organizations deploy high-performance AI at scale.

🔧 With Red Hat AI, you can:

• Use or build optimized foundation models, including Llama, Mistral, Qwen, Gemma, DeepSeek, and others, tailored for performance and accuracy in real-world deployments.
• Customize and fine-tune models for your workflows, from experimentation to production, with tools and frameworks built to support reproducible research and enterprise AI pipelines.
• Maximize inference efficiency across hardware using production-grade compression and optimization techniques like quantization (FP8, INT8, INT4), structured/unstructured sparsity, distillation, and more, ready for cost-efficient deployments with vLLM.
• Confidently deploy validated models on Red Hat AI products.

🔗 Explore relevant open-source tools:

• vLLM – Serve large language models efficiently across GPUs and environments.
• LLM Compressor – Compress and optimize your own models with SOTA quantization and sparsity techniques.
• InstructLab – Fine-tune open models with your data using scalable, community-backed workflows.
• GuideLLM – Benchmark, evaluate, and guide your deployments with structured performance and latency insights.

Or learn more about our full product suite at https://www.redhat.com/en/products/ai