OpenVINO Release Notes#

2024.6 - 18 December 2024#

System Requirements | Release policy | Installation Guides

What’s new#

  • OpenVINO 2024.6 release includes updates for enhanced stability and improved LLM performance.

  • Introduced support for Intel® Arc™ B-Series Graphics (formerly known as Battlemage).

  • Implemented optimizations to improve the inference time and LLM performance on NPUs.

  • Improved LLM performance with GenAI API optimizations and bug fixes.

OpenVINO™ Runtime#

CPU Device Plugin#

  • KV cache now uses asymmetric 8-bit unsigned integer (U8) as the default precision, reducing memory stress for LLMs and increasing their performance. This option can be controlled by model meta data.

  • Quality and accuracy has been improved for selected models with several bug fixes.

GPU Device Plugin#

  • Device memory copy optimizations have been introduced for inference with Intel® Arc™ B-Series Graphics (formerly known as Battlemage). Since it does not utilize L2 cache for copying memory between the device and host, a dedicated copy operation is used, if inputs or results are not expected in the device memory.

  • ChatGLM4 inference on GPU has been optimized.

NPU Device Plugin#

  • LLM performance and inference time has been improved with memory optimizations.

OpenVINO.GenAI#

  • The encrypted_model_causal_lm sample is now available, showing how to decrypt a model.

Other Changes and Known Issues#

Jupyter Notebooks#

Previous 2025 releases#

2024.5 - 20 November 2024

What’s new

  • More GenAI coverage and framework integrations to minimize code changes.

Deprecation And Support#

Using deprecated features and components is not advised. They are available to enable a smooth transition to new solutions and will be discontinued in the future. To keep using discontinued features, you will have to revert to the last LTS OpenVINO version supporting them. For more details, refer to the OpenVINO Legacy Features and Components <https://docs.openvino.ai/2024/documentation/legacy-features.html>__ page.

Discontinued in 2024#

  • Runtime components:

    • Intel® Gaussian & Neural Accelerator (Intel® GNA). Consider using the Neural Processing Unit (NPU) for low-powered systems like Intel® Core™ Ultra or 14th generation and beyond.

    • OpenVINO C++/C/Python 1.0 APIs (see 2023.3 API transition guide for reference).

    • All ONNX Frontend legacy API (known as ONNX_IMPORTER_API).

    • PerfomanceMode.UNDEFINED property as part of the OpenVINO Python API.

  • Tools:

    • Deployment Manager. See installation and deployment guides for current distribution options.

    • Accuracy Checker.

    • Post-Training Optimization Tool (POT). Neural Network Compression Framework (NNCF) should be used instead.

    • A Git patch for NNCF integration with huggingface/transformers. The recommended approach is to use huggingface/optimum-intel for applying NNCF optimization on top of models from Hugging Face.

    • Support for Apache MXNet, Caffe, and Kaldi model formats. Conversion to ONNX may be used as a solution.

    • The macOS x86_64 debug bins are no longer provided with the OpenVINO toolkit, starting with OpenVINO 2024.5.

    • Python 3.8 is no longer supported, starting with OpenVINO 2024.5.

      • As MxNet doesn’t support Python version higher than 3.8, according to the MxNet PyPI project, it is no longer supported by OpenVINO, either.

    • Discrete Keem Bay support is no longer supported, starting with OpenVINO 2024.5.

    • Support for discrete devices (formerly codenamed Raptor Lake) is no longer available for NPU.

Deprecated and to be removed in the future#

  • Intel® Streaming SIMD Extensions (Intel® SSE) will be supported in source code form, but not enabled in the binary package by default, starting with OpenVINO 2025.0.

  • Ubuntu 20.04 support will be deprecated in future OpenVINO releases due to the end of standard support.

  • The openvino-nightly PyPI module will soon be discontinued. End-users should proceed with the Simple PyPI nightly repo instead. More information in Release Policy.

  • The OpenVINO™ Development Tools package (pip install openvino-dev) will be removed from installation options and distribution channels beginning with OpenVINO 2025.0.

  • Model Optimizer will be discontinued with OpenVINO 2025.0. Consider using the new conversion methods instead. For more details, see the model conversion transition guide.

  • OpenVINO property Affinity API will be discontinued with OpenVINO 2025.0. It will be replaced with CPU binding configurations (ov::hint::enable_cpu_pinning).

    • “auto shape” and “auto batch size” (reshaping a model in runtime) will be removed in the future. OpenVINO’s dynamic shape models are recommended instead.

  • Starting with 2025.0 MacOS x86 is no longer recommended for use due to the discontinuation of validation. Full support will be removed later in 2025.