--- title: "segment-anything vs ultralytics" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/facebookresearch-segment-anything-vs-ultralytics-ultralytics" tools: ["facebookresearch-segment-anything", "ultralytics-ultralytics"] --- # segment-anything vs ultralytics *GraphCanon updated Jul 17, 2026* ## Verdict Pick segment-anything if an AI tool for segmentation tasks offering pre-trained models and straightforward integration methods; pick ultralytics if ultralytics is renowned for advanced computer vision tasks including object detection, instance segmentation, and tracking through its YOLO series. [segment-anything](https://github.com/facebookresearch/segment-anything) reports 55k GitHub stars, 6.4k forks, and 595 open issues, last pushed Sep 18, 2024. [ultralytics](https://platform.ultralytics.com) has 59k stars, 11k forks, and 207 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [segment-anything's repository](https://github.com/facebookresearch/segment-anything) and [ultralytics's repository](https://github.com/ultralytics/ultralytics). | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [ultralytics](/tools/ultralytics-ultralytics.md) | | --- | --- | --- | | Tagline | Provides code for running inference with the SegmentAnything Model (SAM). | Object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking | | Stars | 54,520 | 59,357 | | Forks | 6,354 | 11,356 | | Open issues | 595 | 207 | | Language | Jupyter Notebook | Python | | Adopt for | An AI tool for segmentation tasks offering pre-trained models and straightforward integration methods. | Ultralytics is renowned for advanced computer vision tasks including object detection, instance segmentation, and tracking through its YOLO series. | | Persona | - | - | | Runtime | - | - | | License | Apache 2.0 license, permitting free use, modification, and distribution of the source code without requiring derivative works to maintain the same license. | Available under both an open-source AGPL-3.0 license for community and academic use, and a commercial Enterprise License for business integration and production, providing flexibility beyond just open | | Categories | Inference & Serving | Computer Vision | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [segment-anything](/tools/facebookresearch-segment-anything.md) | [ultralytics](/tools/ultralytics-ultralytics.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 661d | 0d | | Open issues (now) | 595 | 207 | | Full report | [trust report](/tools/facebookresearch-segment-anything/trust.md) | [trust report](/tools/ultralytics-ultralytics/trust.md) | **Typed relationship:** segment-anything _(related)_ ultralytics Ultralytics focuses on comprehensive computer vision tasks, including segmentation. Segment Anything Model could be used as a specialized tool for segmentation tasks within the broader Ultralytics suite. ## Shared compatibility - **Python**: [segment-anything](/tools/facebookresearch-segment-anything.md) - Python runtime; [ultralytics](/tools/ultralytics-ultralytics.md) - Python runtime ## Decision facts: segment-anything - **Requirements:** Min 8 GB RAM; Requires Python >=3.8, PyTorch >=1.7 with CUDA recommended for faster performance; Optional dependencies such as OpenCV and ONNX may further enhance functionality but are not always necessary for basic use. - **Adopt for:** An AI tool for segmentation tasks offering pre-trained models and straightforward integration methods. - **License detail:** Apache 2.0 license, permitting free use, modification, and distribution of the source code without requiring derivative works to maintain the same license. ## Decision facts: ultralytics - **Adopt for:** Ultralytics is renowned for advanced computer vision tasks including object detection, instance segmentation, and tracking through its YOLO series. - **License detail:** Available under both an open-source AGPL-3.0 license for community and academic use, and a commercial Enterprise License for business integration and production, providing flexibility beyond just open ## Choose when ### Choose segment-anything if… - segment-anything is primarily Jupyter Notebook; ultralytics is Python. - License: segment-anything is Apache-2.0, ultralytics is AGPL-3.0. - Requirements: Min 8 GB RAM; Requires Python >=3.8, PyTorch >=1.7 with CUDA recommended for faster performance; Optional dependencies such as OpenCV and ONNX may further enhance functionality but are not always necessary for basic use.. - Ultralytics focuses on comprehensive computer vision tasks, including segmentation. Segment Anything Model could be used as a specialized tool for segmentation tasks within the broader Ultralytics suite. - Tags unique to segment-anything: image-processing, jupyter-notebook, pytorch, segmentation. - Also covers Inference & Serving. - When you need precise segmentation in images with varied objects or regions, as SAM provides high-quality mask generation from prompts. ### Choose ultralytics if… - ultralytics is primarily Python; segment-anything is Jupyter Notebook. - License: ultralytics is AGPL-3.0, segment-anything is Apache-2.0. - Ultralytics focuses on comprehensive computer vision tasks, including segmentation. Segment Anything Model could be used as a specialized tool for segmentation tasks within the broader Ultralytics suite. - Tags unique to ultralytics: computer-vision, deep-learning, image-classification, instance-segmentation. - Also covers Computer Vision. - When precision in real-time object detection and segmentation across multiple domains (e.g., robotics, surveillance) is needed. ## When NOT to use segment-anything - Avoid using SAM if your project's constraints specifically require real-time performance since running inference demands significant computational resources. - Do not choose this tool when a lightweight or resource-efficient solution is needed, as it relies on heavyweight pre-trained models that may be unsuitable for devices with limited computing power. ## When NOT to use ultralytics - If a project requires proprietary modifications or integrations where source code contributions must be tightly controlled, as the AGPL-3.0 would require sharing modified versions of Ultralytics. - When deployment scenarios strictly limit the use of open-source software due to compliance or security policies that might conflict with AGPL licensing. ## Common questions ### What is the difference between segment-anything and ultralytics? segment-anything: Provides code for running inference with the SegmentAnything Model (SAM).. ultralytics: Object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking. See the comparison table for live GitHub stats and shared categories. ### When should I choose segment-anything over ultralytics? Choose segment-anything over ultralytics when segment-anything is primarily Jupyter Notebook; ultralytics is Python; License: segment-anything is Apache-2.0, ultralytics is AGPL-3.0; Requirements: Min 8 GB RAM; Requires Python >=3.8, PyTorch >=1.7 with CUDA recommended for faster performance; Optional dependencies such as OpenCV and ONNX may further enhance functionality but are not always necessary for basic use.; Ultralytics focuses on comprehensive computer vision tasks, including segmentation. Segment Anything Model could be used as a specialized tool for segmentation tasks within the broader Ultralytics suite; Tags unique to segment-anything: image-processing, jupyter-notebook, pytorch, segmentation; Also covers Inference & Serving; When you need precise segmentation in images with varied objects or regions, as SAM provides high-quality mask generation from prompts. ### When should I choose ultralytics over segment-anything? Choose ultralytics over segment-anything when ultralytics is primarily Python; segment-anything is Jupyter Notebook; License: ultralytics is AGPL-3.0, segment-anything is Apache-2.0; Ultralytics focuses on comprehensive computer vision tasks, including segmentation. Segment Anything Model could be used as a specialized tool for segmentation tasks within the broader Ultralytics suite; Tags unique to ultralytics: computer-vision, deep-learning, image-classification, instance-segmentation; Also covers Computer Vision; When precision in real-time object detection and segmentation across multiple domains (e.g., robotics, surveillance) is needed. ### When should I avoid segment-anything? Avoid using SAM if your project's constraints specifically require real-time performance since running inference demands significant computational resources. Do not choose this tool when a lightweight or resource-efficient solution is needed, as it relies on heavyweight pre-trained models that may be unsuitable for devices with limited computing power. ### When should I avoid ultralytics? If a project requires proprietary modifications or integrations where source code contributions must be tightly controlled, as the AGPL-3.0 would require sharing modified versions of Ultralytics. When deployment scenarios strictly limit the use of open-source software due to compliance or security policies that might conflict with AGPL licensing. ### Is segment-anything or ultralytics more popular on GitHub? ultralytics has more GitHub stars (59,357 vs 54,520). Stars measure visibility, not whether either tool fits your constraints. ### Are segment-anything and ultralytics open source? Yes - both are open-source projects on GitHub (segment-anything: Apache-2.0, ultralytics: AGPL-3.0). ### Where can I find alternatives to segment-anything or ultralytics? GraphCanon lists graph-backed alternatives at [segment-anything alternatives](/tools/facebookresearch-segment-anything/alternatives) and [ultralytics alternatives](/tools/ultralytics-ultralytics/alternatives) ([segment-anything markdown twin](/tools/facebookresearch-segment-anything/alternatives.md), [ultralytics markdown twin](/tools/ultralytics-ultralytics/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/facebookresearch-segment-anything-vs-ultralytics-ultralytics.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, segment-anything or ultralytics? segment-anything: Dormant. ultralytics: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for segment-anything and ultralytics? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [segment-anything trust report](/tools/facebookresearch-segment-anything/trust); [ultralytics trust report](/tools/ultralytics-ultralytics/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=facebookresearch-segment-anything`](/api/graphcanon/graph?tool=facebookresearch-segment-anything) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_