Head-to-head · Image Annotation Software
CVAT vs FiftyOne
CVAT leads on 0 checks, FiftyOne on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreCVAT · 8.9/10
- Free planonly CVAT
CVAT scores higher on our rubric for image annotation software: 8.9 against 8.6 out of 10; our editors rank them #2 and #5.
CVAT is the better fit for open-source teams needing a complete CV workflow. FiftyOne is the better fit for ML teams combining annotation and model evaluation.
- CVAT fits best
Open-source teams needing a complete CV workflow
- FiftyOne fits best
ML teams combining annotation and model evaluation
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Side by side
| Feature | CVAT 8.9/10 Visit ↗ | FiftyOne 8.6/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 8.9 | 8.6 |
| Ranking | #2 in Image Annotation Software | #5 in Image Annotation Software |
| Best for | Open-source teams needing a complete CV workflow | ML teams combining annotation and model evaluation |
| Pricing model | Free plan + paid | Free |
| Starting price | $23/mo | Free |
| Free plan | ✓ (best) | Not checked yet |
| Free trial | — | — |
| Deployment | Cloud, Self-hosted | Cloud, Self-hosted |
| Platforms | Web | Web, Windows, macOS, Linux |
| Support | Community, Docs | Email, Community, Docs |
| Compliance | GDPR, SSO/SAML | ISO 27001, SSO/SAML |
| Integrations | 5 integrations | 20 integrations |
| Built for | Solo, Small business, Mid-market, Enterprise | Small business, Mid-market, Enterprise |
| Features CVAT 3/3 · FiftyOne 3/3 | ||
| Model-assisted labeling | ✓ | ✓ |
| Team collaboration | ✓ | ✓ |
| API access | ✓ | ✓ |
| Specs | ||
| Annotation types | Rectangle/bounding box, polygon, polyline, points, ellipse, cuboid, skeleton, tag, brush/mask | bounding boxes; polygons; segmentation masks; classifications; polylines; SAM2 click-to-segment instance segmentation |
| Image formats | JPEG, PNG, BMP, GIF, PPM, TIFF | JPEG; PNG; BMP |
| Dataset export | CVAT XML, Datumaro JSON, COCO JSON, YOLO, Pascal VOC, Cityscapes, KITTI, Open Images, MOT, and others | COCO; image directory; image classification directory tree; FiftyOne dataset; Python/CLI export |
| Our review | ||
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| Cons |
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| Our verdict | CVAT is a visual data annotation platform for creating training datasets from images, video, and 3D data. It is aimed at computer vision and AI teams that need manual labeling, AI-assisted detection, segmentation or tracking, dataset… Read the review → |
FiftyOne is an image and multimodal data platform from Voxel51 for computer-vision and machine-learning teams. It combines annotation, dataset curation, model evaluation, review workflows, and dataset export in one environment. Annotation… Read the review → |
Strengths and trade-offs
CVAT — where it wins
- Supports image, video, and 3D annotation with many annotation types
- Offers AI-assisted workflows, REST API, Python SDK, and CLI
- Exports to major computer-vision formats and connects to cloud storage
Where it doesn't
- Free plan supports only 1–2 members
- Solo plans are limited to a personal workspace
- Enterprise deployment starts at $12,000 per year
FiftyOne — where it wins
- Supports boxes, polygons, masks, classifications, polylines, and SAM2 annotation
- Combines annotation, review workflows, dataset curation, and model evaluation
- Offers APIs, self-hosting, exports, and integrations across data systems
Where it doesn't
- Enterprise capabilities are organized around contact-sales plans
- The broad feature set may exceed the needs of simple annotation projects
- Governed collaborative deployments require the Enterprise offering
- CVAT8.9/10 · Free plan
A broad CV workflow spanning manual, AI-assisted, collaborative, and programmatic annotation.
Visit CVATFull verdict → - FiftyOne8.6/10 · Open source
A broad open-source platform for annotation, dataset curation, and model evaluation.
Visit FiftyOneFull verdict →
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All image annotation software comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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