Get your VLM running in 3 simple steps on Intel CPUs

Back to Articles Get your VLM running in 3 simple steps on Intel CPUs Published October 15, 2025 Update on GitHub Upvote 22 +16 Ezequiel Lanza ezelanza Follow Intel Helena helenai Follow Intel Nikita nikita-savelyev-intel Follow Intel Ella Charlaix echarlaix Follow Ilyas Moutawwakil IlyasMoutawwakil Follow With the growing capability of large language models (LLMs), a new class of models has emerged: Vision Language Models (VLMs). These models can analyze images and videos to describe scenes, create captions, and answer questions about visual content. While running AI models on your own device can be difficult as these models are often computationally demanding, it also offers significant benefits: including improved privacy since your data stays on your machine, and enhanced speed and reliability because you're not dependent on an internet connection or external servers. This is where tools like Optimum Intel and OpenVINO come in, along with a small, efficient model like SmolVLM. In this blog post, we'll walk you through three easy steps to get a VLM running locally, with no expensive hardware or GPUs required (though you can run all the code samples from this blog post on Intel GPUs). Deploy your model with Optimum Small models like SmolVLM are built for low-resource consumption, but they can be further optimized. In this blog post we will see how to optimize your model, to lower memory usage and speedup inference, making it more efficient for deployment on devices with ...