ClearML alternatives

4 tools to consider instead of ClearML, shown against it.

ClearML MLflow Weights & Biases Kubeflow Comet
Vendor ClearML (formerly Allegro AI) Linux Foundation (LF AI & Data); originated at Databricks Weights & Biases, Inc. Kubeflow project (CNCF) Comet ML, Inc.
Pricing model Free tier + paid plans Open source + paid options Free tier + paid plans Open source + paid options Free tier + paid plans
Free tier Yes Yes Yes Yes Yes
Deployment Cloud, Self-hosted Cloud, Self-hosted Cloud, Self-hosted Self-hosted Cloud, Self-hosted
Open source Yes (Apache-2.0) Yes (Apache-2.0) No Yes (Apache-2.0) No
Best for Teams wanting a single open-source platform that combines experiment tracking with pipeline orchestration and deployment. Teams wanting free, self-hostable experiment tracking without committing to a vendor's hosted SaaS. Teams wanting a polished, collaborative hosted experiment tracker with an enterprise self-hosting option. Platform teams that already run Kubernetes and want to orchestrate ML pipelines on their own infrastructure. Teams wanting one vendor for both classic experiment tracking and LLM/agent observability.
Pricing

A free hosted Community tier and a fully self-hosted open-source server are both available; Pro adds per-user fees plus usage-based storage/compute, and Scale/Enterprise are custom-quoted for larger or VPC/on-prem deployments.

Community Free
Pro $15/user/month + usage
Scale / Enterprise Custom (VPC or on-prem)

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

MLflow itself is free and open source; any cost comes from the infrastructure or managed platform (e.g. Databricks) you run it on.

Pricing has not been verified yet — see the vendor's site.

Free for individuals; Pro is a flat monthly rate for small teams with usage-based storage and data-ingestion overages; Enterprise and self-hosted plans are custom-quoted.

Free $0/month
Pro From $60/month
Enterprise Custom

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Kubeflow is free, open-source software; costs come from the Kubernetes cluster and cloud infrastructure it runs on.

Pricing has not been verified yet — see the vendor's site.

Free tiers exist on both the core MLOps platform and the Opik LLM product; Pro plans bill per user per month with usage caps, and Enterprise is custom-quoted.

Free (MLOps) $0
Pro (MLOps) $19/user/month
Enterprise Custom

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features
  • Automatic experiment tracking with minimal code changes
  • Pipeline orchestration and job scheduling
  • Dataset versioning (Hyper-Datasets)
  • Model registry and one-click deployment/serving
  • GPU/compute orchestration across on-prem and cloud
  • Self-hosted open-source server
  • Kubernetes integration for enterprise scale
  • Experiment tracking (parameters, metrics, artifacts)
  • Model Registry with staged versioning
  • Reproducible project packaging
  • Model packaging across ML frameworks
  • REST API and CLI for automation
  • Built-in model serving for quick deployment
  • LLM tracing and evaluation
  • Autologging for popular ML frameworks
  • Experiment tracking with interactive dashboards
  • Hyperparameter sweeps
  • Model and dataset Registry with lineage
  • LLM/agent tracing and evaluation (Weave)
  • Team collaboration and reporting
  • CI/CD automations and alerts
  • Self-hosted deployment option
  • Artifact versioning
  • Multi-step ML pipeline orchestration
  • Distributed training operators (TensorFlow, PyTorch, etc.)
  • Managed Jupyter notebook servers
  • Hyperparameter tuning (Katib)
  • Model serving via KServe
  • Runs on any Kubernetes cluster
  • Multi-tenancy and access control for shared clusters
  • Experiment tracking and comparison dashboards
  • Model production monitoring (via Opik)
  • Artifact and dataset versioning
  • Hyperparameter optimization
  • LLM tracing and evaluation (Opik)
  • Team collaboration and reporting
  • Self-hosted and hybrid deployment
  • Custom visualization panels

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