FiftyOne vs V7 Darwin

FiftyOne8.6Visit V7 Darwin8.4Visit

Higher score FiftyOne #5 in Image Annotation Software 8.6/10 Open source ✓ 3 of 3 features Visit FiftyOne

vs

V7 Darwin #7 in Image Annotation Software 8.4/10 Free plan · pricing on request Free plan✓ 3 of 3 features Visit V7 Darwin

• FiftyOne fits best

  ML teams combining annotation and model evaluation

• V7 Darwin fits best

  Teams annotating medical and video imagery

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Side by side

Feature	FiftyOne 8.6/10 Visit ↗	V7 Darwin 8.4/10 Visit ↗
At a glance
Editor score	8.6	8.4
Ranking	#5 in Image Annotation Software	#7 in Image Annotation Software
Best for	ML teams combining annotation and model evaluation	Teams annotating medical and video imagery
Pricing model	Free	Free plan + paid
Starting price	Free	—
Free plan	Not checked yet	✓ (best)
Free trial	—	—
Deployment	Cloud, Self-hosted	Cloud
Platforms	Web, Windows, macOS, Linux	Web
Support	Email, Community, Docs	Community, Docs
Compliance	ISO 27001, SSO/SAML	SOC 2, ISO 27001, GDPR, HIPAA
Integrations	20 integrations	5 integrations
Built for	Small business, Mid-market, Enterprise	Mid-market, Enterprise
Features FiftyOne 3/3 · V7 Darwin 3/3
Model-assisted labeling	✓	✓
Team collaboration	✓	✓
API access	✓	✓
Specs
Annotation types	bounding boxes; polygons; segmentation masks; classifications; polylines; SAM2 click-to-segment instance segmentation	Polygon; bounding box; tag; skeleton; keypoint; line; ellipse; mask; attributes; text; directional vector; instance ID
Image formats	JPEG; PNG; BMP	.jpg, .jpeg, .webp, .png, .bmp, .svs, .tif, .tiff, .qtiff, .dcm, .rvg, .nii, .nii.gz, .ndpi
Dataset export	COCO; image directory; image classification directory tree; FiftyOne dataset; Python/CLI export	Darwin JSON; Darwin XML; COCO; CVAT; YOLO; Semantic PNG; Instance PNG; Pascal VOC; NIfTI
Our review
Pros	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	Supports many annotation types, including masks, skeletons, keypoints, and polygons AI-assisted labeling, model-in-the-loop workflows, and external model integration Video and DICOM interpolation plus multi-stage review and collaboration
Cons	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	Paid pricing uses custom platform fees, user licenses, and volume-based charges Its broad workflow may be more than teams needing simple image labeling The platform is web-based and API-accessible rather than open source
Our verdict	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 →	V7 Darwin is a web-based data-labeling platform for teams creating machine-learning datasets from images, video, medical imaging, microscopy, documents, and other visual data. It is suited to AI teams, research groups, and enterprise… Read the review →

Strengths and trade-offs

• 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

• V7 Darwin — where it wins

  • Supports many annotation types, including masks, skeletons, keypoints, and polygons
  • AI-assisted labeling, model-in-the-loop workflows, and external model integration
  • Video and DICOM interpolation plus multi-stage review and collaboration

  Where it doesn't

  • Paid pricing uses custom platform fees, user licenses, and volume-based charges
  • Its broad workflow may be more than teams needing simple image labeling
  • The platform is web-based and API-accessible rather than open source

• FiftyOne8.6/10 · Open source

  A broad open-source platform for annotation, dataset curation, and model evaluation.

  Visit FiftyOneFull verdict →
• V7 Darwin8.4/10 · Free plan · pricing on request

  A broad annotation platform for teams building computer-vision and medical-imaging datasets.

  Visit V7 DarwinFull verdict →