ClearML vs LUML Flow
ClearML
clear.ml
LUML Flow
luml.aiSide by side
| Figure | ClearML | LUML Flow |
|---|---|---|
| Price from | $15/mo | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 4 | 0 |
| Spec score · ML Experiment Tracking Software | 8.7 (#3) | 7.0 (#27) |
| Headquarters | Berkeley, California, USA | Linz, Austria |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | The page lists PyTorch, LangGraph, XGBoost, scikit-learn, LlamaIndex, TensorFlow, Anthropic, LightGBM, DSPy, JAX, LangChain, and Keras. |
| Open source | ClearML says its self-hosted version is 100% open source on GitHub. | The Flow SDK and UI are described as available in LUML’s public GitHub repository. |
| Support | Scale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services. | The Flow page links to documentation and offers a request-demo link. |
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.