ClearML
7.4#1 in gpu cluster management softwareFrom $15 a monthFree planWebAPILinuxmacOS
VisitClearML vs Opik
What both publish
| Fact | ClearML | Opik |
|---|---|---|
| Headquarters | Berkeley, California, USA | New York City, United States |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | The integration catalog covers TypeScript, Python, Java, .NET and Ruby ecosystems plus no-code tools and OpenTelemetry. |
| Open source | ClearML says its self-hosted version is 100% open source on GitHub. | The core observability and evaluation feature set is available as open-source code that users can download and run locally. |
| Support | Scale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services. | The pricing page lists community and self-service support across plans, email support for Pro and Enterprise, and dedicated support and SLAs for Enterprise. |
ClearML plans
- CommunityFree
- Pro$15 a month
- EnterprisePriced on request
- ScalePriced on request
Opik plans
- Free CloudFree
- Open SourceFree
- Pro Cloud$19 a month
- EnterprisePriced on request
Pick ClearML if…
ClearML suits AI and machine-learning teams that need experiment management and model development tools alongside GPU resource management. Its hosting choices may also suit teams with self-hosted, VPC, on-premises, or hybrid requirements.
Pick Opik if…
Opik is for teams building LLM applications or agents that need tracing, evaluation, and production monitoring. Its free plans are described as suitable for development and testing.