ClearML vs mlop
ClearML
clear.ml
mlop
mlop.aiSide by side
| Figure | ClearML | mlop |
|---|---|---|
| Price from | $15/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 3 |
| Spec score · ML Experiment Tracking Software | 8.7 (#3) | 7.5 (#18) |
| 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 compares experiments, model versions, hyperparameters, metrics, artifacts, and gradients. |
| Product | ClearML describes its AI infrastructure platform as three layers: Infrastructure Control Plane, AI Development Center, and GenAI App Engine. | mlop describes itself as an open source experiment tracking platform for machine learning teams. |
| 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 includes email support for Pro and 24/7 support from founders for Enterprise. |
Plans
ClearML
- CommunityFree
- Pro$15 a month
- EnterprisePriced on request
- ScalePriced on request
In their own words
ClearML
ClearML is an AI infrastructure platform organized into an Infrastructure Control Plane, AI Development Center, and GenAI App Engine. The Control Plane manages GPU resources across on-premises, cloud, and hybrid environments, including multi-tenant GPU-as-a-Service. The Development Center supports developing, training, testing, and deploying AI/ML models, with monitoring, pipelines, a model repository, and CI/CD integration. The GenAI App Engine deploys LLMs on compute clusters and provides networking, authentication, access control, and monitoring. Experiment tracking, comparisons, artifacts, metrics and plots, and Git version control integration appear across the listed tiers. Integrations include PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain; storage integrations include AWS S3, Azure, Google Storage, MinIO, and Backblaze B2. ClearML can be hosted on its servers, self-hosted, or provided as a managed service, with VPC, on-premises including air-gapped, and hybrid options. Community is free; Pro costs $15 a month per user plus usage. Scale and Enterprise pricing is by quote.