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Chapter 2. Validated model support levels

Red Hat AI ships models at two support levels: validated and enabled. Understanding these support levels helps you make informed decisions about which models to deploy for your inference workloads.

Validated models

Red Hat has tested validated models with GuideLLM performance benchmarking and Language Model Evaluation Harness accuracy evaluations across specific OpenShift Container Platform, Red Hat OpenShift AI, and Red Hat AI Inference version combinations.

Validated models are benchmarked for specific use cases. This can include inference performance, quality, and other benchmarks. All third-party models are governed by the third-party license of the original model provider.

Validated models include general-purpose large language models such as Llama, Granite, Mistral, Qwen, and Phi model families, and quantized variants in FP8, INT4, INT8, NVFP4, and BF16 formats.

Enabled models

Red Hat ships enabled models as modelcar container images with architecturally compatible configurations. Enabled models have not completed the full benchmarking and accuracy evaluation pipeline that validated models receive.

Enabled models include specialty categories such as:

  • Embedding models, for example granite-embedding-english-r2, all-MiniLM-L6-v2, nomic-embed-text-v1.5, and Qwen3-Embedding-8B
  • Safety and guard models, for example Llama-Guard-4-12B and granite-guardian-3.2-5b
  • Security models, for example Foundation-Sec-8B-Instruct
  • Reasoning models, for example Phi-4-reasoning
  • Additional general-purpose models not yet through the full validation pipeline

Both support levels indicate that Red Hat ships the model and provides support. The key difference is the depth of testing: validated models have quantified performance and accuracy data for specific platform configurations, while Red Hat verifies that enabled models work with the inference server architecture.

To find the support level for a specific model, see Model support matrix.

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