Ultralytics has unveiled YOLO26, a groundbreaking advancement in computer vision AI designed specifically for edge and low-power environments. As the most advanced iteration of its YOLO series, YOLO26 introduces a fully end-to-end, NMS-free architecture that eliminates traditional post-processing steps, significantly reducing latency and simplifying deployment across cloud, edge, and embedded systems. Built from the ground up for real-world performance, YOLO26 is optimized for use in robotics, manufacturing automation, smart cities, logistics, healthcare, retail, and other fields where hardware constraints and efficiency are critical. By removing the need for non-maximum suppression (NMS) and other fragile inference stages, the model delivers state-of-the-art accuracy with faster, more reliable performance on CPUs, edge accelerators, and embedded devices. Glenn Jocher, Founder and CEO of Ultralytics, emphasized the transformative nature of the new model. “YOLO26 is the fastest and most deployable object detection system available in the world today,” he said. “By removing entire stages of the inference pipeline, we’ve eliminated the complexity that has long held back edge deployment.” Jing Qiu, Senior Machine Learning Engineer and lead author of YOLO26, highlighted its architectural breakthroughs. “YOLO26 achieves stronger stability, faster inference, and unmatched hardware portability without compromising accuracy. This is a major leap forward for production-ready vision AI.” YOLO26 is released as a unified multi-task model family capable of handling object detection, instance segmentation, classification, pose estimation, and oriented object detection—all within a single framework. This allows teams to streamline workflows from research to production, reducing the need for multiple models and simplifying integration. In addition, Ultralytics introduced YOLOE-26, a new family of open-vocabulary segmentation models built on the YOLO26 foundation. YOLOE-26 supports text prompts, visual prompts, and prompt-free segmentation, offering greater flexibility and accuracy than previous models. It seamlessly integrates into existing workflows and is available across all standard YOLO sizes. The release continues Ultralytics’ legacy of open-source innovation. YOLO models are already used over 2.5 billion times daily by developers worldwide. With over 123,000 GitHub stars and 205 million Python package downloads, the YOLO series remains the most widely adopted vision AI framework. Ultralytics has partnered with leading hardware providers including Axelera AI, Intel, DEEPX, and Sony AITRIOS to ensure optimal performance across advanced AI platforms. YOLO26 is available through the Ultralytics platform with full support for training, inference, and export. Enterprise licensing is also offered for commercial and closed environments, supporting scalable production deployment and long-term maintenance. For more information and to access YOLO26, visit platform.ultralytics.com/ultralytics/yolo26.