SAM 3 vs YOLOv7

Compare SAM 3 and YOLOv7 side-by-side.

Compare SAM 3 vs YOLOv7 live

Run the same image across every model that supports a task and compare their outputs side-by-side.

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

Meta

SAM 3 vs YOLOv7: Overview

SAM 3

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.

YOLOv7

YOLOv7 is a real-time object detection model developed by Chien-Yao Wang and Hong-Yuan Mark Liao at Academia Sinica, released in July 2022 under the GPL-3.0 license. It introduces Extended Efficient Layer Aggregation Networks (E-ELAN) for improved gradient flow in the backbone, and trainable bag-of-freebies techniques including coarse-to-fine lead guided label assignment and auxiliary heads that improve accuracy without adding inference cost.

YOLOv7 achieves 56.8% AP on COCO at 30 FPS on a V100 GPU at the time of release, establishing a strong accuracy-speed tradeoff among real-time detectors. It supports detection, instance segmentation, and pose estimation variants. YOLOv7 is deployable through Roboflow Inference and the standard training pipeline in the official repository.

SAM 3 vs YOLOv7 Comparison Table

PropertySAM 3YOLOv7
OrganizationMetaAcademia Sinica
Categoryclosedopen
Modalitymultimodalvision
Release DateNov 2025Jul 2022
Context Window
Parameters6.2M-151.7M
LicenseProprietaryGPL v3
Vision Tasks
Object DetectionDemo
Instance Segmentation
Promptable Concept SegmentationDemo
Video Object Tracking
Zero Shot Segmentation
Model Features
Foundation Vision
Real-Time Vision
Zero-shot Detection