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SPECIFICTION
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ClearML vs Lamin

ClearML

clear.ml

Lamin

lamin.ai

Side by side

FigureClearMLLamin
Price from$15/mo$20/mo
Free planYesYes
Free trial—Yes
Open source——
WebYesYes
WindowsYes—
macOSYes—
LinuxYes—
APIYesYes
Self-hostedYesYes
Plans published44
Spec score · ML Experiment Tracking Software8.7 (#3)8.3 (#6)
HeadquartersBerkeley, California, USAMunich and New York City
IntegrationsThe integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations.Documented integrations include Claude Code, GitHub Copilot, Cursor, Git, Nextflow with Seqera, PyTorch Lightning, Weights & Biases, MLflow, and Vitessce.
ProductClearML describes its AI infrastructure platform as three layers: Infrastructure Control Plane, AI Development Center, and GenAI App Engine.LaminDB is described as an open-source, format-agnostic lakehouse and programmable memory layer for R&D.
StorageClearML documents storage integrations for AWS S3, Azure, Google Storage, and other S3-compatible services, including MinIO and Backblaze B2.Documented read/write storage includes local filesystems, AWS S3, S3-compatible services such as MinIO and Cloudflare R2, and Google Cloud Storage; HTTP/HTTPS and Hugging Face are read-only.

Plans

ClearML

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

ClearML pricing →

Lamin

  • FreeFree
  • Pro$20 a month
  • Enterprise$200 a month
  • Team$200 a month

Lamin 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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Lamin

LaminDB is Lamin's open-source, format-agnostic lakehouse and programmable memory layer for research and development. It tracks data, code and agent activity across notebooks, scripts and workflows, and provides schema-based records for LIMS and ELN use cases, including ontologies and notes. Users can validate and annotate datasets, then manage changes through branching and versioning data and code. Documented integrations include Claude Code, GitHub Copilot, Cursor, Git, Nextflow with Seqera, PyTorch Lightning, Weights & Biases, MLflow and Vitessce. Read/write storage includes local filesystems, AWS S3, S3-compatible services such as MinIO and Cloudflare R2, and Google Cloud Storage; HTTP/HTTPS and Hugging Face are read-only. Lamin provides web, API and self-hosted options. The Free plan is free for open assets and public database queries, with no hosted database listed. Pro is $20 a month billed annually. Team and Enterprise are each $200 a month billed annually per seat; Enterprise includes full on-prem deployment in the customer's AWS account. Lamin says it is SOC 2 certified and encrypts Lamin-managed deployments in transit and at rest. The maker was founded in 2022 and is headquartered in Munich and New York City.

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