> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/datasets/annotate/annotate/ai-labeling.md).
# AI Labeling
Use AI tools to speed up your labeling process.
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AI Labeling features use credits at the rates listed on our [credits page](https://roboflow.com/credits).
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Roboflow offers four AI-powered labeling features to help speed up your Workflow:
* [Label Assist](/datasets/annotate/annotate/ai-labeling/model-assisted-labeling.md): Use a model you have already trained to auto-label images in your dataset.
* [Smart Select](/datasets/annotate/annotate/ai-labeling/smart-select.md): Use the Segment Anything Model in your browser to annotate polygon masks with a single click.
* [Box Prompting](/datasets/annotate/annotate/ai-labeling/box-prompting-ai-labeling.md): Draw examples of an object in an image, then let Box Prompting find all other instances of that object in the image.
* [Auto Label](/datasets/annotate/annotate/ai-labeling/auto-label.md): Use a foundation model (GPT-6 Astra, SAM 3, or Gemini), a trained model, or a saved Workflow to auto-label all images in your dataset.
We recommend each solution in the following cases:
* **Label Assist**: Ideal for labeling data once you already have a trained model.
* **Smart Select:** Ideal for labeling the first version of your dataset, adding new annotations that Label Assist missed, or adding annotations for new classes to a dataset.
* **Box Prompting**: Ideal if you have lots of similar objects to label in an image (i.e. if you are labeling individual screws on a tray with dozens of the same screw).
* **Auto Label**: Ideal if you need to label common objects (i.e. a vehicle) in bulk.
You can find out more about each option on their respective documentation pages.
### Supported AI Labeling Tools by Project Type
### Supported Model Types for Use In Label Assist
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