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SAM 3 vs SAM 3D Objects

Compare SAM 3 and SAM 3D Objects side-by-side.

Compare SAM 3 vs SAM 3D Objects 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 SAM 3D Objects Comparison Table

Evals updated October 8, 2026Pricing updated October 9, 2026

PropertySAM 3SAM 3D Objects
OrganizationMetaMeta
Categoryopenopen
Modalitymultimodalvision
Release DateNov 2025Nov 2025
Context Window——
ParametersUnknownUnknown
LicenseCustomCustom
Vision Tasks
Instance SegmentationSupportedSupported
3D ReconstructionNot listedSupported
Object DetectionDemoNot listed
Open Vocabulary Object DetectionSupportedNot listed
Promptable Concept SegmentationDemoNot listed
Video Object TrackingSupportedNot listed
Zero Shot SegmentationSupportedNot listed
Model Features
Foundation VisionSupportedSupported
Multimodal VisionSupportedNot listed
Zero-shot DetectionSupportedNot listed

SAM 3 vs SAM 3D Objects: 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.

SAM 3D Objects

SAM 3D Objects is a 3D reconstruction model released on November 19, 2025 by Meta AI as part of the broader SAM 3 release. It extends the Segment Anything Model family from 2D segmentation into 3D object reconstruction, predicting geometry, texture, and spatial layout for individual objects from a single RGB image. Given an image together with a prompt identifying the object (a segmentation mask, point, or bounding box), the model outputs a full textured 3D mesh, without requiring multi-view captures, depth sensors, or known camera parameters.

SAM 3D Objects uses a two-stage transformer architecture: a coarse stage that predicts 3D shape and object pose, followed by a refinement stage that adds texture and surface detail, with DINOv2 used to encode the input image. The model is trained via a human-and-model-in-the-loop data engine that combines synthetic 3D assets with real-image annotations, producing approximately 3.14 million mesh annotations across nearly 1 million images. Meta released SAM 3D Objects alongside SAM 3D Body, a companion model for single-image human mesh recovery, and SAM 3D Artist Objects (SA-3DAO), a new evaluation benchmark assembled with artist-created 3D ground truth. The model is designed as a companion to SAM 3 for downstream applications including augmented reality, robotics, content creation, and visual effects; it already powers the View in Room feature on Facebook Marketplace. SAM 3D Objects is released under the SAM 3 license; users should review the license terms prior to commercial use.