RF-DETR Segmentation vs Segment Anything Model 2 (SAM 2)
We don't benchmark RF-DETR Segmentation or Segment Anything Model 2 (SAM 2) on Vision Evals. Both are open-weight under Apache 2.0, so either is free for commercial use.
Compare RF-DETR Segmentation vs Segment Anything Model 2 (SAM 2) 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.
RF-DETR Segmentation vs Segment Anything Model 2 (SAM 2) Comparison Table
| Property | RF-DETR Segmentation | Segment Anything Model 2 (SAM 2) |
|---|---|---|
| Organization | Roboflow | Meta |
| Category | open | open |
| Modality | vision | vision |
| Release Date | Oct 2025 | Jul 2024 |
| Context Window | — | — |
| Parameters | 33.6M-38.6M | 38.9M-224.4M |
| License | Apache 2.0 | Apache 2.0 |
| Commercial use | free for commercial use | free for commercial use |
| Model Sizes input resolution per size variant | ||
| Nano | 312×312 | Not available |
| Small | 384×384 | Not available |
| Medium | 432×432 | Not available |
| Large | 504×504 | Not available |
| XL | 624×624 | Not available |
| 2XL | 768×768 | Not available |
| Vision Tasks | ||
| Instance Segmentation | Demo (COCO) | Supported |
| Model Features | ||
| Real-Time Vision | Supported | Not listed |
RF-DETR Segmentation vs Segment Anything Model 2 (SAM 2): 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. Every size is Apache 2.0, so it's commercially usable out of the box: you can ship it in closed-source, commercial products without paying a license fee or open-sourcing your code. 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.
SAM 2 is a real-time image and video segmentation model developed by Meta AI, released in July 2024 under the Apache 2.0 license. It extends the original Segment Anything Model to support video inputs by introducing a streaming memory architecture that maintains object state across frames, enabling consistent segmentation of objects through occlusion, motion, and scene changes. For image inputs, SAM 2 operates similarly to its predecessor with improved mask quality and speed.
SAM 2 accepts point, box, and mask prompts and produces object masks interactively or in a fully automated mode. Its memory architecture enables video segmentation at real-time speeds. SAM 2 is used in annotation pipelines, video analysis, robotic perception, and any application requiring high-quality promptable segmentation across both images and video.