SAM 3 vs YOLOv5

Released on November 19th, 2025, Segment Anything 3 (SAM 3) is a zero-shot image segmentation model that “detects, segments, and tracks objects in images and videos based on concept prompts.” This model was developed by Meta as the third model in the Segment Anything series.

Unlike its previous SAM models (Segment Anything and Segment Anything 2), you can provide SAM 3 with the prompt “shipping container” and it will generate precise segmentation masks for all shipping containers in an image. SAM 3 generates segmentation masks that correspond to the location of the objects found with a text prompt.

YOLOv5 is an object detection model developed by Ultralytics, released in June 2020 under the AGPL-3.0 license. It is implemented in PyTorch and introduced a more accessible and well-documented YOLO implementation compared to earlier Darknet-based versions, with an integrated training and export pipeline supporting a wide range of deployment targets. YOLOv5 uses a CSP backbone, PANet neck, and a single-stage detection head with anchor-based regression.

YOLOv5 is available in five sizes from Nano to Extra Large and supports export to ONNX, TensorRT, CoreML, and other formats. It is one of the most widely deployed object detection models in production environments and remains a common starting point for custom detection model training due to its documentation, community support, and compatibility with Roboflow Inference.