Segment Anything Model (SAM) vs YOLO11

The Segment Anything Model is a promptable image segmentation foundation model developed by Meta AI, released in April 2023 under the Apache 2.0 license. It introduces a general-purpose segmentation architecture trained on SA-1B, a dataset of over 1 billion masks across 11 million images collected using a data engine that leveraged the model itself. SAM accepts point, bounding box, and mask prompts and generates high-quality segmentation masks for any object in an image, including objects not seen during training.

SAM achieves strong zero-shot performance across a wide range of segmentation tasks and domains. Its promptable interface makes it suitable as a building block for automated annotation, interactive segmentation tools, and integration with detection models such as Grounding DINO. SAM has been extended by subsequent works including SAM 2, SAM 3, and Grounded-SAM.

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.