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SPECIFICTION
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ClearML vs Rubicon-ML

ClearML

clear.ml

Rubicon-ML

capitalone.github.io

Side by side

FigureClearMLRubicon-ML
Price from$15/moFree
Free planYesYes
Free trial——
Open source——
WebYesYes
WindowsYes—
macOSYes—
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published41
Spec score · ML Experiment Tracking Software8.7 (#3)8.3 (#7)
HeadquartersBerkeley, California, USAMcLean, Virginia, United States
IntegrationsThe integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations.The documentation includes integrations for Git, Prefect, and Scikit-learn.
SupportScale includes private Slack channel support and an SLA, while Enterprise includes white-glove support with a custom SLA and professional services.The project README directs users to open a GitHub issue to report a bug or make a suggestion.

Plans

ClearML

  • CommunityFree
  • Pro$15 a month
  • EnterprisePriced on request
  • ScalePriced on request

ClearML pricing →

Rubicon-ML

  • rubicon-mlFree

Rubicon-ML pricing →

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.

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Rubicon-ML

Rubicon-ML is a free, open-source Python package for capturing model training and execution details. It records inputs, outputs, parameters, and outcomes in searchable projects and experiments, while Git integration can attach repository origin, branch, and commit information for auditability. Its dashboard and widgets let users explore, filter, visualize, compare, and share logged work. Multiple experiments can be logged in parallel, and asynchronous S3 communication keeps network reads and writes from blocking. Storage backends include local files, Amazon S3, in-memory storage, and Weights & Biases. Integrations are provided for Git, Prefect, and Scikit-learn; RubiconPipeline can log parameters and metrics when Scikit-learn pipelines are fit and scored. Installations use pip or conda-forge. Visualization is an optional pip extra, while conda installs optional extras by default. The dashboard is a Dash app that can be dockerized, and remote logging does not require a hosted server. It is licensed under Apache License 2.0.

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