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OpenVINO Model Server 2026.3.1

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@dtrawins dtrawins released this 31 Aug 13:21
· 1 commit to releases/2026/3 since this release
v2026.3.1
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This is a hotfix release including minor changes in the server component and a few improvements from OpenVINO Runtime.

Improvements included:

  • Corrections in input validation for KServer and audio endpoints
  • Fixed structured output generation including # char in the content
  • Addressed security vulnerabilities
  • Updated OpenVINO Runtime to 2026.3.1 version
  • Kokoro model can be used with NPU accelerator
  • Gemma4 model has accuracy improvements

Known issues:

  • Model Qwen3.6-27B is supported only when exported via optimum-intel with OpenVINO 2026.3 version. The default version in https://huggingface.co/OpenVINO/Qwen3.8-27B-int4-ov fails to load unless branch 2026.3.1 is used. The latest weekly package drop and docker image openvino/model_server:weekly don't have such limitation
  • Model Muse-Glimmer-30B is supported without native tool parsing. Tool parser has been added to 2026.4.0. The latest weekly package drop and docker image openvino/model_server:weekly don't have such limitation
  • OMNI models are supported as a preview feature with limitations - MOE models are not supported yet, concurrency is not possible - requests will be queued in processing.
  • NPU execution on LLM has a limit on max prompt parameter 8k tokens. Model will fail to load with higher parameter. It is expected to be fixed in next release.
  • NPU plugin for Qwen3-embeddings and Qwen4-reranking fails to load the model when allowed context exceeds 8k tokens. In order to user such models, the workaround is to edit config.json in the model folder and set "max_position_embeddings" to be below 8k. It is expected to be fixed in next release.

You can use OpenVINO Model Server public Docker images based on Ubuntu via the following command:

  • docker pull openvino/model_server:2026.3.1 - CPU device support with image based on Ubuntu 24.04
  • docker pull openvino/model_server:2026.3.1-gpu - GPU, NPU and CPU device support with image based on Ubuntu 24.04

or use provided binary packages. Only packages with suffix _python_on have support for python.

There is also additional distribution channel via https://storage.openvinotoolkit.org/repositories/openvino_model_server/packages/2026.3.1/

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