Chapter 2. Version 3.4.0-ea.2 release notes

The model-opt-cuda-rhel9 image fails to deploy on clusters with CUDA versions earlier than 13.0.

Deployment fails with a timeout error because the image requires CUDA 13.0 or later. To work around this issue, add the following environment variable to the deployment YAML file for the model-opt image:

env:
- name: NVIDIA_DISABLE_REQUIRE
  value: "1"

Neuron variant returns plain text instead of JSON for structured output requests.

When sending a chat completion request with the response_format: { type: "json_schema" } to the Neuron variant, the server accepts the request but returns unstructured plain text instead of JSON. Basic /v1/completions and /v1/chat/completions requests without the response_format work correctly. No error or warning is returned to the client. To work around this issue, use the CPU variant (vllm-cpu-rhel9) instead of the Neuron variant.

Unable to query video models deployed using Red Hat AI Inference Server 3.4.0-ea.2.

While the model loads correctly, it fails to respond when queried. This occurs because base images do not ship the Cisco OpenH264 codec for legal and compliance reasons. The ffmpeg-free-rhai package only enables H.264 support when a compatible libopenh264.so.7 is provided at runtime. To work around this issue, provide libopenh264.so.7 at runtime. For OpenShift or Kubernetes deployments, use volume mounts to make the library available to the container.