# Meta Segment Anything Model 2 (SAM 2)

According to OpenAITools.app telemetry verified on 2026-11-10, Meta Segment Anything Model 2 (SAM 2) (ai.meta.com) is an AI platform indexed under AI Image Segmentation (ranked #29 globally) generating 5.36M monthly visits with a month-over-month traffic delta of +1.69M (+46.1%). Its primary geographic market is United States (37.5% traffic share), and it operates on a Free pricing model. Top competing alternatives by monthly volume include Ultralytics (793.42K visits/mo), Unsloth AI (887.46K visits/mo), Stable Diffusion (Stability AI) (341.87K visits/mo).

Meta's open model for promptable object segmentation in images and video

## Key Telemetry & Specifications

| Metric | Value |
| :--- | :--- |
| Tool Name | Meta Segment Anything Model 2 (SAM 2) |
| Handle | meta-segment-anything-model-2 |
| Status | active |
| Origin | official |
| Maintenance | active |
| Official Domain | ai.meta.com |
| Website URL | https://ai.meta.com/SAM2 |
| Categories | AI Image Segmentation, Open Source AI Models, AI Models |
| Pricing Model | Free |
| Monthly Visits | 5,357,056 |
| MoM Traffic Change | 1,690,096 |
| MoM Growth Rate | +46.1% |
| Primary Market | United States |
| Market Share | 37.5% |
| Direct Visits | 508,543 |
| Organic Search Visits | — |
| Social Visits | — |
| Referral Visits | 213,127 |
| Email Visits | 20,710 |
| Review Score | 4.8 |
| Saved Count | 2 |
| Supported Platforms | Website |
| Billing Platforms |  |
| Attributes | Features: Website; Pricing: Free |
| Tags | Image segmentation, Video segmentation, Object tracking, AI model, Machine learning, Open source, Zero-shot learning, Interactive segmentation |

## Overview

SAM 2 keeps the interaction that made the first Segment Anything Model popular — point at, box or mask the thing you want — and stretches it to the time dimension. A per-session memory module stores information about the target object, so the model can follow it through subsequent frames even when it is briefly occluded or leaves the frame, and additional prompts on any frame refine the predicted mask. When the input is a still image the memory is empty and behaviour falls back to classic SAM.

The architecture is a streaming one that processes video frames one at a time, enabling real-time interactive applications and efficient batch processing. Meta reports state-of-the-art results, with improvements over SAM on image segmentation and stronger video object segmentation than prior models, particularly on object parts, while requiring less user interaction. Training data includes SA-V, a large video segmentation dataset of roughly 600K masklets over about 51K videos collected across 47 countries, which Meta open sourced alongside the model.

The release is deliberately open-innovation oriented: a pretrained model, the SA-V dataset, example code and a browser demo are published so researchers and developers can build on it. Typical uses include video editing and effects, dataset annotation, robotics and perception pipelines, medical or scientific imaging workflows, and as a segmentation front end for other generative or editing systems. Users should note that Meta publishes model cards describing intended use, fairness evaluations and limitations, and that commercial usage of the weights is governed by the license Meta attaches to the release.

## Pricing & Plans

Free. SAM 2 is released as open research: pretrained model weights, code and the SA-V dataset are downloadable at no cost, and the interactive web demo is free to use. The only costs are your own compute or your chosen third-party hosting.

## Key Features & Capabilities

- **One model for images and video:** The first unified, promptable segmentation model that handles both still images and video, using clicks, boxes or masks as input prompts.
- **Memory-based object tracking:** A per-session memory module keeps context on the target object, tracking it across frames and recovering when the object is temporarily hidden from view.
- **Refine predictions interactively:** Add correction prompts on any frame to fix or adjust the mask, supporting iterative, human-in-the-loop annotation workflows in real time.
- **Open weights, code and SA-V dataset:** Pretrained checkpoints, reference code and the SA-V video segmentation dataset are published to let the research community build and benchmark on top.
- **Strong zero-shot behaviour:** Performs well on objects, images and videos never seen during training, making it usable across domains without fine-tuning.

## Primary Use Cases

- **Rotoscoping and effects (Video editors and VFX artists):** Click an object once and track it through a clip to produce masks for compositing, background replacement or stylistic effects without manual frame-by-frame work.
- **Segmentation benchmarking (ML researchers):** Use the released weights, SA-V dataset and evaluations as a strong baseline for video object segmentation, tracking and interactive annotation research.
- **Faster labeling pipelines (Data and annotation teams):** Seed masks with a few prompts and refine them per frame, cutting the manual effort of producing pixel-accurate labels for training data.
- **Perception building block (Robotics and vision engineers):** Embed promptable segmentation and tracking into perception or editing systems, or feed the outputs into downstream generative and analysis models.

## Strengths

- Unified image and video segmentation in a single, promptable model
- Open weights, code and the large SA-V dataset available for free
- Real-time streaming inference enables genuinely interactive workflows
- Strong zero-shot accuracy and less interaction time than prior interactive video methods

## Limitations

- Weights and dataset are intended primarily for research use; commercial terms depend on the release license
- Running the model at scale requires your own GPU infrastructure
- Segmentation quality can still degrade with very fast motion, heavy occlusion or unusual video domains

## Frequently Asked Questions

### Is SAM 2 free to use?
Yes. Meta publishes SAM 2 as open research, so the pretrained model, code and SA-V dataset can be downloaded at no charge and the interactive demo is free. You only cover your own compute or hosting.

### What is the difference between SAM and SAM 2?
SAM segmented objects in a single image. SAM 2 adds a memory mechanism so the same promptable workflow extends to video, tracking an object across frames with the ability to correct masks on any frame.

### Can I use SAM 2 commercially?
Meta releases the weights, code and dataset under its own research-oriented license and model card. Teams planning commercial deployment should review the specific license terms published with the release before shipping.

### Where can I try SAM 2 without installing anything?
Meta hosts an interactive web demo where you can upload or choose a video and click an object to track it. The model code and checkpoints are separately available for local or cloud deployment.

### What is Meta Segment Anything Model 2 (SAM 2)'s monthly traffic and growth trend?
Meta Segment Anything Model 2 (SAM 2) currently receives 5.36M monthly visits, with a month-over-month traffic change of +1.69M (+46.1% growth rate). Its primary source market is United States (37.5% share), including 508.54K direct visits/mo and — organic search visits/mo.

### Is Meta Segment Anything Model 2 (SAM 2) free? What is its pricing model?
Meta Segment Anything Model 2 (SAM 2) operates on a Free pricing model. Free. SAM 2 is released as open research: pretrained model weights, code and the SA-V dataset are downloadable at no cost, and the interactive web demo is free to use. The only costs are your own compute or your chosen third-party hosting. Supported billing and checkout platforms include: not listed.

### What are the best Meta Segment Anything Model 2 (SAM 2) alternatives in 2026?
Based on OpenAITools.app category traffic and feature fit, the top five alternatives to Meta Segment Anything Model 2 (SAM 2) are: 1. Ultralytics (793.42K visits/mo); 2. Unsloth AI (887.46K visits/mo); 3. Stable Diffusion (Stability AI) (341.87K visits/mo); 4. Civitai (6.96M visits/mo); 5. Pruna AI (229.28K visits/mo).

### Which platforms and core AI capabilities does Meta Segment Anything Model 2 (SAM 2) support?
Meta Segment Anything Model 2 (SAM 2) is classified under AI Image Segmentation, Open Source AI Models, AI Models, supports the following platforms: Website, and its core capability tags include: Image segmentation, Video segmentation, Object tracking, AI model, Machine learning, Open source.

## Alternatives

| Tool Name | Monthly Visits | Pricing Model | Compare |
| :--- | :--- | :--- | :--- |
| [Ultralytics](https://openaitools.app/tool/ultralytics) | 793,423 | Freemium | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-ultralytics) |
| [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | Free | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-unsloth-ai) |
| [Stable Diffusion (Stability AI)](https://openaitools.app/tool/stable-diffusion) | 341,872 | Freemium, Contact for Pricing | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-stable-diffusion) |
| [Civitai](https://openaitools.app/tool/civitai) | 6,963,136 | Freemium | [Compare](https://openaitools.app/compare/civitai-vs-meta-segment-anything-model-2) |
| [Pruna AI](https://openaitools.app/tool/pruna-ai) | 229,282 | Paid | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-pruna-ai) |
| [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | Freemium, Contact for Pricing | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-roboflow) |
| [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | Paid | [Compare](https://openaitools.app/compare/atlas-cloud-vs-meta-segment-anything-model-2) |
| [AI/ML API](https://openaitools.app/tool/ai-ml-api) | 232,946 | Pay-as-you-go credits (free to start); enterprise custom pricing on request | [Compare](https://openaitools.app/compare/ai-ml-api-vs-meta-segment-anything-model-2) |
| [ModelScope](https://openaitools.app/tool/modelscope-community) | 3,085,423 | Free | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-modelscope-community) |
| [Bagel](https://openaitools.app/tool/bagel) | 7,329 | Free | [Compare](https://openaitools.app/compare/bagel-vs-meta-segment-anything-model-2) |
| [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | Paid | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-replicate-ai) |
| [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | Freemium, Paid | [Compare](https://openaitools.app/compare/meta-segment-anything-model-2-vs-together-ai) |

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Source: https://openaitools.app/tool/meta-segment-anything-model-2