ClearML
7.4#1 in gpu cluster management softwareFrom $15 a monthFree planWebAPILinuxmacOS
VisitClearML vs Valohai
What both publish
| Fact | ClearML | Valohai |
|---|---|---|
| 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 pricing page says Valohai can be deployed as a managed cloud service, on premises, in a private cloud, or in air-gapped environments. |
| Experiment tracking | The pricing page lists experiment tracking, comparisons, artifacts, metrics and plots, and Git version control integration across Open Source, Free/Pro, and Scale/Enterprise tiers. | The platform tracks and versions ML experiments to support reproducibility. |
| Headquarters | Berkeley, California, USA | Turku, Finland |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | Its ecosystem lists a Hugging Face template and connectors for Snowflake, BigQuery, and Redshift, plus Slurm cluster management integration. |
| Support | Scale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services. | Subscriptions include technical support from the Customer Engineering team, along with training and onboarding resources. |
ClearML plans
- CommunityFree
- Pro$15 a month
- EnterprisePriced on request
- ScalePriced on request
Valohai plans
- Valohai subscriptionPriced 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 Valohai if…
Valohai suits ML teams building, testing, and deploying models while coordinating experiments, data, pipelines, and compute. It supports cloud, private, on-premises, and air-gapped deployment needs.