CVAT and Roboflow

CVAT is an open-source annotation tool, Roboflow takes you from labeling to deployment

CVAT vs Roboflow? Over 2 million engineers create datasets, train models, and deploy with Roboflow, and every plan, including the Free tier, comes with self-hosted inference, model weights download, and a private workspace.

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Computer vision system with annotations identifying potatoes and a 'greening' defect on a conveyor belt.

Why are companies choosing Roboflow?

Roboflow is enterprise vision AI infrastructure, used by more than half of the Fortune 100, with SOC 2 Type II, HIPAA, and air-gapped deployment. Create datasets, train models, and deploy to production.

  • End-to-End Vision, One Platform

    From labeling to deployment - build, train, and launch with ease.

  • Built for Builders, Ready for Anything

    Interoperable infrastructure for developers to create custom vision solutions.

  • AI at the Edge, Without Limits

    Deploy seamlessly to any edge device and power real-time vision AI.

  • Roboflow Annotate labeling cans with AI box prompting

    Fast data labeling

    Label data quickly with a suite of AI-assisted annotation tools to augment human labeling or fully automate your data labeling pipeline.

  • Workflow blocks for notifications and integrations

    Build vision AI applications with ease

    Use a low-code open source platform to simplify building and deploying vision AI applications.

  • A team reviewing a detected pallet in a warehouse aisle

    Machine learning expertise, always

    Work with account-dedicated AI specialists and Field Engineers to accelerate development and optimize performance.

  • Photos from datasets across industries

    Datasets and models for every industry

    Access thousands of datasets and pre-trained models to kickstart your computer vision projects.

  • Logos of OpenAI, Microsoft, Meta, Anthropic, Google and Qwen

    Flexible model licensing

    Choose from a range of licensing options to fit your needs, whether for commercial use, private deployment, or collaboration across teams.

Want to migrate from CVAT to Roboflow?

  • Import images to Roboflow

    Bring COCO, YOLO, or CVAT XML exports into Roboflow for model training.

  • Deploy with Roboflow

    No matter where you train your model, use Roboflow's trusted deployment solutions.

  • Automate data labeling

    Use AI labeling in Roboflow to automate 90% of human labeling.

OK I’m ready, how do I use Roboflow?

Roboflow makes it easy to build, train, and deploy custom computer vision models, even if you’re not a machine learning expert.

Start a free Roboflow account

Talk to a Vision AI engineer about going from CVAT to production

Bring us your annotation project and we'll map the path from labels to a deployed model.

Ask us about:

  • Import of your CVAT exports, with labels intact
  • A live demo of Auto Label on your own images
  • Training and deployment in one hosted platform, with no servers to maintain
  • Deployment options: cloud, VPC, on-prem, edge, or air-gapped

Over 80,000 organizations build with Roboflow.

  • Rivian
  • Pella
  • Chobani
  • USG Corporation
  • BNSF Railway
  • American Woodmark
Start where you are

Compare CVAT and Roboflow

CVAT (opens in a new tab) is an open-source annotation platform with self-hosted and managed cloud options. It offers detailed image and video labeling, AI-assisted annotation, and quality review. Its focus is producing training data. Once the annotations are ready, your team still needs tools to train a model, evaluate its performance, and turn its predictions into a working application.

Roboflow connects those steps in one platform. Bring your images and existing CVAT annotations in a supported format such as COCO or YOLO, create a versioned dataset, and train a custom model. For new images, Auto Label (opens in a new tab) drafts annotations from a text prompt for review. Your team can move from correcting labels to comparing model accuracy and latency in the same workspace.

Roboflow Agent helps carry that model into an application: selecting models, building Workflows, and connecting predictions to alerts and business systems. The Roboflow MCP server and ChatGPT plugin (opens in a new tab) let your team manage datasets, start labeling jobs, train models, and test predictions through a conversation or coding agent. Deploy the resulting application to Roboflow’s cloud or your own hardware.

The connection continues after deployment. When your model misses an object or flags an acceptable product, Vision Events lets your team inspect the prediction alongside the image and send useful examples back into training. Labeling becomes part of an ongoing improvement process, connected to how the application performs in production.

Enterprise teams get SSO, role-based permissions, annotation history, labeling analytics, and review workflows to manage access and label quality. Optional labeling services and hands-on engineering support help teams handle large datasets and move applications into production.

Start for free with private projects, unlimited seats, supported model weight downloads, and 10 credits each month. Self-hosted inference is free on every plan, with no Roboflow credits consumed by local inference. Bring a CVAT export, train your first model, and test it on images it hasn’t seen before.

CVAT vs Roboflow Annotate: Feature by Feature

FeatureRoboflow AnnotateCVAT
Supported labeling tasksObject detection, segmentation, classification, keypoint, multimodalObject detection, instance segmentation, keypoints, classification, 3D cuboids
Running environmentWeb browser, no installWeb browser; self-host with Docker or use CVAT Online
Free tierYes, with free self-hosted inference, model weights download, and a private workspaceLimited (1 GB, 3 tasks; SAM tools demo-only)
Open sourceYes, open-source supervision and inference libraries that run alongside the Roboflow platformYes (MIT license)
Hosted labeling environmentYesYes (CVAT Online) or self-host
AI auto labelingYes, Auto Label from a text promptPaid tiers, via Hugging Face or Roboflow-hosted models, or your own AI Agents
Label assist with foundation modelsYes, Smart Polygon powered by Segment AnythingPaid tiers, SAM and SAM 3 click and box prompts
Label assist with custom modelsYes, any model trained or uploaded to RoboflowYes, via self-hosted Nuclio functions or AI Agents on your hardware
Dataset managementYes, versioning, train/valid/test splits, health check, preprocessingBasic, projects and tasks with cloud storage integration
Semantic dataset searchYesNo
Dataset analyticsYesLimited
Labeling analyticsYesEnterprise only
Labeling historyYesNo
Image augmentationYesNo
Export formats40+ formats24 formats (COCO, VOC, YOLO, CVAT XML, MOT, KITTI, etc.)
Role-based access controlYesYes
SSOYesEnterprise only
Model trainingYesNo
Model deploymentYesNo
Application builderYes, Roboflow WorkflowsNo
Model architecturesYes, RF-DETR, YOLO (v8 / v11 / v26), Detectron2, and other current architecturesNo, there is no native model training or model registry
Self-hosted inference serverYes, open-source inference server for custom and foundation modelsNo, the SDK covers tasks, jobs, and annotations, not model serving
Open-source CV libraryYes, supervision for detections, tracking, annotation, and evaluationNo comparable library
SDKs and APIsYes, Python SDK plus REST/HTTP APIsYes, cvat-sdk and cvat-cli on PyPI, plus a REST API and webhooks
ComplianceSOC 2 Type II, HIPAA with BAAs, and PCI DSSNo SOC 2 or ISO 27001 certification, per CVAT's enterprise page

Best CVAT Alternatives

Roboflow is the top CVAT alternative for teams that want labeling, training, and deployment in one platform. Teams comparing CVAT also look at: