Compare CVAT and OpenLLMetry on pricing, features, platforms, and ratings — both AI Infrastructure & MLOps tools, Free / Open Source with Freemium SaaS tiers…
At a Glance
CVAT
OpenLLMetry
Primary category
AI Infrastructure & MLOps
AI Infrastructure & MLOps
Rating
Not documented
Not documented
Pricing model
Free / Open Source with Freemium SaaS tiers
Open Source
Starting price
Free
Free (SDK); optional Traceloop hosted platform has a free tier with paid plans custom-priced
Free plan
Yes
Not documented
Free trial
Not documented
Not documented
Platforms
Web
Not documented
Team collaboration
Not documented
Not documented
AI features
Yes
Yes
Public API
Yes
Yes
Pricing Compared
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
CVAT
Free — $0 N/A
Solo — $33/month ($23/month annual) Monthly or annual
Team — $33/user/month ($23/user/month annual) Monthly or annual, minimum 2 seats
Enterprise (Self-Hosted) — From $12,000/year Annual
OpenLLMetry
OpenLLMetry SDK — Free N/A
Traceloop Free Forever — $0/month Monthly
Traceloop Enterprise — Custom Custom
Pros & Cons
CVAT
Pros
Free and open source (MIT license) with full self-hosting option
Strong video annotation and object-tracking/interpolation tools
Wide dataset format support for ML pipelines
Active open-source community and OpenCV endorsement
Learning curve for teams new to annotation workflows
Paid SaaS tiers add up per seat at larger team sizes
Enterprise self-hosted tier pricing starts fairly high
OpenLLMetry
Pros
Fully open source and free under the Apache 2.0 license
Extremely fast to integrate with one-line instrumentation
Vendor-neutral OpenTelemetry foundation avoids lock-in
Large and fast-growing adoption with 500,000-plus monthly installs
Backed by ServiceNow's resources following the 2026 acquisition
Cons
Full monitoring and evaluation platform requires a paid Traceloop plan beyond free-tier limits
Free tier data retention is limited to 24 hours
Enterprise pricing for the hosted platform is not publicly listed
Relatively young product line launched in 2022
Post-acquisition roadmap integration with ServiceNow introduces some uncertainty for standalone users
Use Cases
CVAT
Autonomous vehicle and robotics training data — Labeling large volumes of image and video data for perception models.
Medical imaging annotation — Self-hosting CVAT to maintain full data sovereignty over sensitive imaging data.
Retail and agriculture computer vision datasets — Annotating shelf, inventory, crop or livestock imagery for applied ML models.
OpenLLMetry
Debugging LLM application behavior — AI engineering teams use OpenLLMetry to trace and debug unexpected LLM outputs, latency spikes, and failures in production.
Enterprise AI governance — Enterprises adopting AI at scale use OpenLLMetry traces to feed governance and compliance workflows.
Rapid observability for AI startups — Startups building LLM-powered products add OpenLLMetry to quickly gain tracing and cost visibility without building custom instrumentation.