YOLO11 vs YOLOv8 Instance Segmentation

YOLO11 is an object detection and multi-task vision model developed by Ultralytics, released in September 2024 under the AGPL-3.0 license. It is the latest generation in the Ultralytics YOLO series and supports object detection, instance segmentation, image classification, pose estimation, and oriented bounding box detection within a single unified framework. YOLO11 introduces architectural refinements that improve accuracy while reducing parameter count compared to YOLOv8 at equivalent model sizes.

YOLO11 is available in five model sizes from Nano to Extra Large and is deployable through the Ultralytics Python package, Roboflow Inference, and export formats including ONNX, TensorRT, and CoreML. It supports fine-tuning on custom datasets through the standard Ultralytics training API.

YOLOv8 Instance Segmentation is the segmentation variant of the YOLOv8 model developed by Ultralytics, released in January 2023 under the AGPL-3.0 license. It extends the standard YOLOv8 detection head with a mask prediction branch that generates pixel-level segmentation masks for each detected object using a prototype mask approach. This enables real-time instance segmentation within a single forward pass.

YOLOv8 Instance Segmentation shares the same backbone and neck architecture as the base detection model and is available in the same size range. It is deployable through Roboflow Inference and supports fine-tuning on custom COCO-format segmentation datasets. It is suited for applications requiring both object localization and precise mask prediction at real-time speeds.