Intel Builds The PC Industry’s Most Robust AI PC Toolchain

What Is The News?

Intel announced it surpassed 500 AI models running optimized on new Intel® Core™ Ultra processors – the industry’s premier AI PC processor available in the market today, featuring new AI experiences, immersive graphics and optimal battery life.

Thanks to Intel’s investments in client AI, AI PC transformation, optimizations of frameworks, and AI tools like the OpenVINOTM toolkit, we’ve reached this major milestone. The 500 models are accessible through several well-known industry sources, such as OpenVINO Model Zoo, Hugging Face, ONNX Model Zoo, and PyTorch. They can be used across the CPU, GPU, and NPU. Object identification, computer vision, picture classification/segmentation, big language, diffusion, and super-resolution are some of the local AI inferencing categories that the models include.

“Intel has a rich history of working with the ecosystem to bring AI applications to client devices, and today we celebrate another strong chapter in the heritage of client AI by surpassing 500 pre-trained AI models running optimized on Intel Core Ultra processors. This unmatched selection reflects our commitment to building not only the PC industry’s most robust toolchain for AI developers, but a rock-solid foundation AI software users can implicitly trust.”

–Robert Hallock, Intel vice president and general manager of AI and technical marketing in the Client Computing Group

Why Does This News Matter?

As part of its mission to foster and promote the AI PC transition, Intel has reached a significant milestone by surpassing 500 AI models. With more AI models, frameworks, and runtimes enabled than any other processor vendor, the Intel Core Ultra processor not only has the fastest-growing AI PC sales in a single quarter compared to competing processors in all of 2023, but it also provides the most robust platform for AI PC development overall. Artificial intelligence (AI) upgraded software capabilities, such as object removal, picture super resolution, and text summarization, rely on models. The ability to bring a wide range of AI features to market is directly related to the number of enabled or optimized models. The design of the feature is impossible in the absence of a model. If optimization is not done during runtime, the feature will not perform to its maximum potential.


1. Enhanced Performance: AI models optimize software stack layers, enabling AI-driven applications to perform efficiently with improved stability and capabilities.

2. Efficient Data Analysis: AI models analyze vast data sets, drawing conclusions and facilitating informed actions, enhancing decision-making processes.

3. Versatile Functionality: AI models empower developers to create AI PC features across text, speech, audio, images, enhancing user experiences and productivity.

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