Intel OpenVINO 发布: 2026.1.0

来源摘要

### Summary of major features and improvements * #### More GenAI coverage and framework 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 * 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