Private Vision AI: Run Reka Edge Entirely on Your Machine

Reka just released Reka Edge, a compact but powerful vision-language model that runs entirely on your own machine. No API keys, no cloud, no data, leaving your computer. I work at Reka, and putting together this tutorial was genuinely fun; I hope you enjoy running it as much as I did. In three steps, you'll go from zero to asking an AI what's in any image or video. What You'll Need A machine with enough RAM to run a 7B parameter model (~16 GB recommended) Git uv, a fast Python package manager. Install it with: curl -LsSf https://astral.sh/uv/install.sh | sh. This works on macOS, Linux, and Windows (WSL). If you're on Windows without WSL, grab the Windows installer instead. Step 1: Get the Model and Inference Code Clone the Reka Edge repository from Hugging Face. This includes both the model weights and the inference code: git clone https://huggingface.co/RekaAI/reka-edge-2603 cd reka-edge-2603 Grab a coffee while it downloads, the model weights are several GB. Step 2: Fetch the Large F