Models
CVAT vs. Label Studio

CVAT vs. Label Studio

Learn how CVAT and Label Studio compare in terms of supported task types, enterprise features like SSO and RBAC, and more.

Tools

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CVAT

CVAT is an open source computer vision labeling tool that also offers a managed annotation solution.
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Label Studio

Label Studio is an open source image annotation tool with support for detection, segmentation, and more.
Supported Vision Task Types

Object detection, instance segmentation, keypoints, classification

Object detection, instance segmentation, keypoints, classification

Offers SSO?
No
Yes
Offers Role-Based Access Control (RBAC)?
Yes
Yes
Dataset Analytics Support
Limited
Limited
Labeling History Support
No
No
Semantic Dataset Search
No
No
Image Augmentation Support
No
No
Offers Foundation Model Label Assistant?
Model Training Offered?
No
No
Deployment Offered?
No
No
Offers a Interactive Vision Application Builder?
No
No
How to buy
Online & Sales
Online & Sales

Compare CVAT and Label Studio

When it comes to comparing CVAT and Label Studio, both are open-source annotation tools that deliver robust support for core vision tasks including object detection, instance segmentation, keypoints, and classification. Both platforms are free to use, support team collaboration, and offer role-based access control. 

CVAT, created by Intel, excels at frame-by-frame image and video labeling with features like interpolation between keyframes, shortcut-driven workflows, and a managed labeling option when you need scale. While Label Studio offers a more polished interface with built-in support for SSO and role-based access control, plus a broader scope beyond vision - handling text, audio, and time-series data.

There are a few key differences to consider:

Label Studio’s enterprise features like SSO make it better suited for larger teams, while CVAT’s annotation speed and frame interpolation are ideal for video-centric workflows. Both integrate well with external platforms, such as Roboflow, for advanced model training, augmentation, and deployment, so you can build a seamless end-to-end vision pipeline as your project grows.