RF-DETR Segmentation vs SAM 3
Compare RF-DETR Segmentation and SAM 3 side-by-side.
Compare RF-DETR Segmentation 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
RF-DETR Segmentation vs SAM 3: Overview
RF-DETR Segmentation is a real-time instance segmentation model developed by Roboflow, with a preview base model released in October 2025 under the Apache 2.0 license and the full variant family — Nano through 2XL — released in January 2026. It extends the RF-DETR object detection architecture with a segmentation head inspired by MaskDINO, enabling pixel-level object delineation while maintaining the real-time performance characteristics of the base model. It is deployable through Roboflow Inference and the open-source rfdetr Python package.
RF-DETR Segmentation supports fine-tuning on custom COCO- or YOLO-format instance segmentation datasets and is benchmarked on Microsoft COCO. It is suited for applications requiring both precise object masks and real-time inference, such as robotic manipulation, quality control, and augmented reality overlays.
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.
RF-DETR Segmentation vs SAM 3 Comparison Table
| Property | RF-DETR Segmentation | SAM 3 |
|---|---|---|
| Organization | Roboflow | Meta |
| Category | open | closed |
| Modality | vision | multimodal |
| Release Date | Oct 2025 | Nov 2025 |
| Context Window | — | — |
| Parameters | 33.6M-38.6M | |
| License | Apache 2.0 | Proprietary |
| Vision Tasks | ||
| Instance Segmentation | Demo (COCO) | |
| Object Detection | Demo | |
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Zero Shot Segmentation | ||
| Model Features | ||
| Foundation Vision | ||
| Real-Time Vision | ||
| Zero-shot Detection | ||