CVAT alternative for image annotation teams that stopped self hosting
ImageLabeling is a hosted CVAT alternative for teams that label images and no longer want to run a CVAT server or pay CVAT Online per seat. You get AI pre-labels for boxes, polygons, masks and keypoints, a labeler and reviewer workflow with consensus, frozen dataset versions and COCO, YOLO and Pascal VOC export. The Team plan covers 10 seats for 149 USD a month, or 74 USD billed yearly. If you label video with tracking or 3D point clouds, CVAT still covers more.
What is the best CVAT alternative for a team that labels images?
For image only work, a hosted tool with flat pricing is usually the better trade. Self hosted CVAT costs nothing in license fees, but somebody on your team owns the Docker stack, upgrades, backups, user accounts and the GPU node for automatic annotation. CVAT Online removes the server work and charges 33 USD per user a month on its Team plan, so the bill grows with every labeler you add.
ImageLabeling sits between those two. Nothing to host, and the price is set by the plan, not by headcount: up to 10 people on Team, 30 on Business. The image annotation workflow page shows each step from upload to export.
CVAT vs ImageLabeling for image annotation
CVAT Online figures come from cvat.ai/pricing/cloud as read in October 2026. Self hosted Enterprise support is quoted by CVAT sales.
| What you compare | CVAT | ImageLabeling |
|---|---|---|
| How you run it | Self hosted with Docker on your own servers, or CVAT Online in the cloud | Hosted, nothing to install |
| Paid entry plan | Solo at 33 USD a month or 23 USD billed yearly, one personal workspace | Starter at 49 USD a month or 24 USD billed yearly, 3 seats |
| Team pricing | 33 USD per user a month, or 23 USD per user billed yearly, minimum 2 seats | Flat plan, 10 seats on Team at 149 USD a month, 30 seats on Business at 499 USD |
| AI assisted labeling | SAM 2 and SAM 3 tools, model integrations, internal AI calls counted per month by plan | AI pre-labels for your own classes, 1,000 to 35,000 images a month by plan |
| Review | Manual review jobs, ground truth jobs and honeypots | Labeler then reviewer flow, consensus from Team, QA scores per labeler on Business |
| SSO | Team plan, annual billing only | Google and Microsoft SSO on Business, SAML SSO on Enterprise |
| Video and 3D | Video with interpolation and tracking, 3D point cloud cuboids | Images only, video frames can be uploaded as images |
| Export formats | Long list of formats including CVAT XML, COCO, YOLO and Pascal VOC | COCO JSON, YOLO txt with data.yaml, Pascal VOC XML and CSV |
| Who maintains it | Your team on self hosted, CVAT on Online | ImageLabeling |
| Managed labeling | Separate labeling services from the CVAT team | Monthly retainer on Business and Enterprise |
What an 8 person labeling team pays on each
Take a team with 2 ML engineers and 6 labelers who all need an account, labeling about 3,000 new images a month.
On self hosted CVAT the license line is zero, but the real cost moves to your own payroll and cloud bill: an engineer who keeps the instance patched and backed up, the VM and storage, and a GPU if you want automatic annotation at speed. For a team whose engineers should be training models, that time usually costs more than a flat plan. Plans and limits are side by side on the image annotation tool pricing page.
| Item | CVAT Online Team | ImageLabeling Team |
|---|---|---|
| Monthly billing | 8 seats at 33 USD, 264 USD a month | 149 USD a month |
| Yearly billing | 8 seats at 23 USD, 184 USD a month | 74 USD a month, 888 USD a year |
| Adding 2 more labelers | Plus 66 USD a month on monthly billing | Included, up to 10 seats |
| AI assistance | Internal AI calls within the plan quota | 3,500 AI pre-labeled images a month |
| Server work | None on Online | None |
When CVAT is still the better choice
We would rather you pick the right tool the first time. Stay on CVAT if one of these is true.
In those cases ImageLabeling would cover only part of your work.
- You label video and rely on interpolation and object tracking across frames.
- You annotate 3D point clouds from lidar with cuboids.
- Your security rules say training data never leaves your own servers, and you have staff to run CVAT on premises.
- You need an unusual export format that CVAT supports and your pipeline depends on it.
- You are one researcher working alone, where the Solo plan or a local install is enough.
When a hosted CVAT alternative fits better
Teams comparing several hosted tools can read the same comparison for the Roboflow alternative and the Labelbox alternative.
- Your CVAT server is maintained by whoever has time, and an upgrade or a full disk has already stopped labeling for a day.
- You add labelers for a project and do not want the bill to rise with each account.
- You train detection, segmentation or keypoint models on photos, and images are the only data you label.
- You want AI pre-labels on every new batch without setting up a model server and a GPU yourself.
- You need a review step with consensus and per labeler QA scores that a manager can read without opening the admin panel.
How to move a project from CVAT
Most teams move one project in an afternoon.
- In CVAT, open the project or task and export the dataset as COCO 1.0, with or without images.
- Upload the same images to a new ImageLabeling project and import the COCO file. Images match by file name and CVAT labels become classes in your schema.
- Send the imported labels to review, so reviewers check old work before it enters a version.
- Run AI pre-labels on the images that were never labeled, then freeze a dataset version.
- Export COCO or YOLO for the next training run. The COCO annotation tool page explains how IDs and categories are kept, and the YOLO labeling tool page covers data.yaml and splits.
Teams that move image labeling off CVAT
- Manufacturing quality teams labeling defect photos every week, see defect detection datasets.
- Robotics teams that retrain pick and place models for every release, see robotics dataset labeling.
- Agtech teams that bring in seasonal labelers during harvest and drop them afterwards.
- Startups whose CVAT box was set up by an engineer who has since left.
FAQ
What are the alternatives to CVAT?
The common CVAT alternatives are Label Studio for self hosted multi data labeling, Roboflow for a platform that also trains and deploys models, Labelbox, SuperAnnotate, Encord and V7 for enterprise and multimodal work, and ImageLabeling for hosted image annotation with flat pricing. Pick by data type first, then by how you want to pay.
How much does CVAT cost?
CVAT Online has a free plan, Solo at 33 USD a month or 23 USD billed yearly, and Team at 33 USD per user a month or 23 USD per user billed yearly with a minimum of 2 seats, as of October 2026. Enterprise and self hosted support are quoted. The self hosted open source version has no license fee.
Is CVAT good for a team?
CVAT works well for teams that label video or 3D data and can maintain it. For image only teams, the costs show up elsewhere: server upkeep on self hosted CVAT, or a per seat bill on CVAT Online that grows with every labeler. A hosted tool with seats included in the plan is easier to budget.
Can I import CVAT annotations into ImageLabeling?
Yes. Export your CVAT project or task as COCO 1.0, upload the same images to ImageLabeling and import the COCO file. Boxes, polygons and classes arrive as editable objects, so reviewers can check them before you freeze the next dataset version.
Does ImageLabeling support video annotation like CVAT?
No. ImageLabeling labels images only. You can extract frames and label them as images, but there is no video timeline with interpolation or tracking. If video is a large part of your work, CVAT or another video capable tool is the better fit.
Can I try ImageLabeling before I buy?
Yes. The demo on the homepage labels one of your own images with AI pre-labels you can edit, with no account needed. Plans start at 24 USD a month billed yearly, and you can cancel anytime.
Label one of your CVAT images now
Drop an image from your current CVAT project into the demo and see the AI pre-labels and the editor before you move a single file.