ClearML
7.4#1 in gpu cluster management softwareFrom $15 a monthFree planWebAPILinuxmacOS
VisitClearML vs MLRun
What both publish
| Fact | ClearML | MLRun |
|---|---|---|
| Deployment options | ClearML says its platform can be hosted on its servers, self-hosted, or provided as a managed service, with VPC, on-premises including air-gapped, and hybrid options. | The documented deployment options are Kubernetes, an AWS cluster, an Azure AKS cluster and Iguazio's managed service. |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | The ecosystem lists GitHub Actions, GitLab CI/CD, Jenkins and Kubeflow Pipelines for CI/CD integration. |
| Support | Scale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services. | The open-source offering includes community support, while managed MLRun includes 24/7 enterprise support, service monitoring and log management. |
ClearML plans
- CommunityFree
- Pro$15 a month
- EnterprisePriced on request
- ScalePriced on request
MLRun plans
- Open Source MLRunFree
- Managed MLRun on IguazioPriced 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 MLRun if…
You want what its maker publishes above — check its page for the details.