Intel® Distribution of OpenVINO™ Toolkit

What’s New

• More Gen AI coverage and frameworks integrations to minimize code changes

• New models supported on CPUs & GPUs: Qwen3 VL
• New models supported on CPUs: GPT-OSS 120B
• Preview: Introducing the OpenVINO backend for llama.cpp, which enables optimized inference on Intel CPUs, GPUs, and NPUs. Validated on GGUF models such as Llama-3.2-1B-Instruct-GGUF, Phi-3-mini-4k-instruct-gguf, Qwen2.5-1.5B-Instruct-GGUF, and Mistral-7B-Instruct-v0.3.
• New notebook: Unified VLM chatbot with video file support and interactive model switching across Qwen3-VL, Qwen2.5-VL, and LLaVa-NeXT-Video.
• Broader LLM model support and more model compression techniques
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  • OpenVINO™ GenAI adds TaylorSeer Lite caching for image and video generation, accelerating diffusion-transformer inference across Flux, SD3, and LTX-Video pipelines, aligned with Hugging Face Diffusers.
  • LTX-Video generation on GPU achieves end-to-end acceleration through fusion of RMSNorm and RoPE operators, significantly improving video generation performance.
  • OpenVINO™ GenAI adds dynamic LoRA support for Qwen3-VL and VL models with LLM, allowing developers to swap adapters at runtime for efficient serving of multiple model variants in production without reloading the base model.
  • Preview: The release-weights API for ov::Model enables memory reclamation during model compilation on NPUs, delivering dramatically lower peak memory consumption for edge and client deployments. Users must set this property in ov::Model, and it will be applied during compilation.
• More portability and performance to run AI at the edge, in the cloud or locally

• Introducing support for Intel® Core™ Series 3 processors (formerly codenamed Wildcat Lake) and Intel® Arc™ Pro B70 Graphics with 32GB memory for single-GPU inference on 20-30B parameter LLMs
• Prompt Lookup Decoding extended to vision-language pipelines, delivering significantly faster token generation for multimodal workloads on Intel CPUs and GPUs.
• OpenVINO™ GenAI now has a smaller runtime footprint after eliminating ICU DLL dependencies from tokenization, leading to reduced memory usage, faster startup, and easier deployment.
• OpenVINO GenAI introduces WhisperPipeline for Node.js via its NPM package, delivering production-ready speech recognition with word-level audio-to-text transcription.
• OpenVINO™ Model Server enhances support for Qwen3-MOE and GPT-OSS-20b models, delivering improved performance, accuracy, and robust concurrent request handling with continuous batching. These pre-optimized models are available on Hugging Face for easy deployment. Additionally, the Model Server introduces image inpainting and outpainting capabilities via the /image endpoint for AI image editing.

Get all the details. See 2026.1 release notes.

Installation instructions

You can choose how to install OpenVINO™ Runtime from Archive* according to your operating system:

• Install OpenVINO Runtime on Linux*
• Install OpenVINO Runtime on Windows*
• Install OpenVINO Runtime on macOS*

What's included in the download package (Archive File)

• Offers both C/C++ and Python APIs
• Additionally includes code samples

Helpful Links

NOTE: Links open in a new window.

• Home Page
• Download
• All Documentation, Guides, and Resources
• OpenVINO Notebooks
• Release Notes
• Community Forum
• File an Issue on GitHub*