Grounding DINO vs SAM 3
Compare Grounding DINO and SAM 3 side-by-side.
Compare Grounding DINO vs SAM 3 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
Grounding DINO vs SAM 3: Overview
Grounding DINO is an open-vocabulary object detection model developed by IDEA Research, released in March 2023 under the Apache 2.0 license. It extends the DINO transformer-based detector with grounded pre-training, enabling it to detect arbitrary objects described by free-form text queries rather than a fixed set of predefined categories. The model integrates a text encoder with a visual backbone through a feature fusion module that aligns language and visual representations at multiple scales.
Grounding DINO achieves strong zero-shot detection performance on COCO, LVIS, and ODinW benchmarks, and supports referring expression comprehension tasks. It is widely used as a foundation for open-vocabulary detection pipelines and as the detection backbone in systems such as Grounded-SAM. The model is particularly suited for applications requiring flexible, text-driven object localization across diverse domains.
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.
Grounding DINO vs SAM 3 Comparison Table
| Property | Grounding DINO | SAM 3 |
|---|---|---|
| Organization | IDEA Research | Meta |
| Category | open | closed |
| Modality | vision | multimodal |
| Release Date | Mar 2023 | Nov 2025 |
| Context Window | — | — |
| Parameters | 172M-341M | |
| License | Apache 2.0 | Proprietary |
| Vision Tasks | ||
| Object Detection | Demo | |
| Instance Segmentation | ||
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Zero Shot Segmentation | ||
| Model Features | ||
| Foundation Vision | ||
| Zero-shot Detection | ||