ClearML vs ZenML
ClearML
clear.mlZenML
zenml.ioSide by side
| Figure | ClearML | ZenML |
|---|---|---|
| Price from | $15/mo | $999/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 3 |
| Spec score · ML Experiment Tracking Software | 8.7 (#3) | 7.8 (#11) |
| Spec score · Model Registry Software | 8.7 (#3) | 7.8 (#10) |
| Spec score · MLOps Platforms | 8.7 (#3) | 7.8 (#7) |
| Spec score · Model registries | 8.7 (#8) | 8.4 (#9) |
| Headquarters | Berkeley, California, USA | Munich, Germany |
| Infrastructure | The Infrastructure Control Plane manages GPU resources across on-premises, cloud, and hybrid environments and supports multi-tenant GPU-as-a-Service. | Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting the code. |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | The integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines. |
| 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 plan includes community support, Scale includes priority support, and Enterprise includes dedicated support with an SLA. |
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.
ZenML
ZenML orchestrates AI and machine-learning pipelines and agents written in Python. Pipelines can run on Kubernetes, Vertex AI, SageMaker, AzureML, or a laptop without rewriting code. ZenML versions step outputs such as models and evaluation datasets, supports re-execution from any step, and reuses cached results when code and inputs have not changed. Deployment choices include local, SaaS, and self-hosted setups, with Docker and Kubernetes Helm methods. ZenML says it stores metadata while data, artifacts, and compute remain in the customer's infrastructure or VPC. Its integrations directory lists 66 tools, including LangGraph, OpenAI Agents SDK, PyTorch, MLflow, AWS, and Google Cloud Vertex AI Pipelines. The self-hosted Open Source plan is free and includes unlimited executions and projects. Scale costs $999 a month and includes 2,000 executions, three projects, and five snapshots. Enterprise has custom pricing and adds SSO, custom-role RBAC, audit logs, and air-gapped deployment. ZenML says it is SOC 2 Type II and ISO 27001 certified.