SAM 3 vs YOLO World
Compare SAM 3 and YOLO World side-by-side. See how these vision models stack up in Object Detection.
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Models in this comparison
SAM 3 vs YOLO World Comparison Table
Evals updated July 24, 2026Pricing updated July 25, 2026
| Property | SAM 3 | YOLO World |
|---|---|---|
| Organization | Meta | Tencent AI Lab |
| Category | open | open |
| Modality | multimodal | multimodal |
| Release Date | Nov 2025 | Feb 2024 |
| Context Window | — | — |
| Parameters | 13M | |
| License | Custom | GPL v3 |
| Vision Tasks | ||
| Object Detection | Demo | Demo |
| Open Vocabulary Object Detection | ||
| Instance Segmentation | ||
| Phrase Grounding | ||
| Promptable Concept Segmentation | Demo | |
| Video Object Tracking | ||
| Zero Shot Segmentation | ||
| Model Features | ||
| Multimodal Vision | ||
| Zero-shot Detection | ||
| Foundation Vision | ||
| Real-Time Vision | ||
SAM 3 vs YOLO World: Overview
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.
YOLO-World v2 Small (YOLO-World-S-v2) is the smallest variant of Tencent AI Lab’s YOLO-World v2 family, released around February 2024 under GPL-v3. With ~13 million parameters, it adopts a prompt-then-detect paradigm using offline vocabularies and is pretrained on large-scale datasets such as Objects365 and GoldG. The model processes image inputs at 640×640 or 1280×1280 resolutions and supports zero-shot open-vocabulary object detection, enabling recognition of novel categories from text prompts without retraining.
Evaluations show competitive results across benchmarks like LVIS and COCO, while maintaining real-time efficiency. On an NVIDIA V100, the small variant reaches ~74 FPS at standard resolutions. Together with larger YOLO-World v2 models, it provides a scalable framework for efficient, open-vocabulary detection across diverse deployment settings.
Frequently Asked Questions
SAM 3 is released under Custom, while YOLO World uses GPL v3. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.
Yes. The comparison demo on this page runs both models on the same image side by side for object detection in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.