Side by side
ClearML vs Metaflow
Both stand on ml experiment tracking software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan APILinuxMac+3
ClearML combines AI/ML development tooling with infrastructure and GenAI deployment capabilities, and offers both self-hosted and managed deployment paths. Compare plan limits and usage charges with your team's GPU and project needs.
Visit ClearML Free plan Open source APILinuxMac+2
Metaflow offers a path from local workflow work to deployments using cloud or Kubernetes infrastructure. The local-only setup is limited, so production scaling requires infrastructure in a cloud account or Kubernetes cluster.
Visit MetaflowThe facts
| ClearML | Metaflow | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Yes |
| Runs on | API, Linux, Mac, Self-hosted, Web, Windows | API, Linux, Mac, Self-hosted, Web |
| Lowest paid plan | Pro: $15 per user a month | Free or on request |
| Plans published | 4 | 1 |
| Maker | Not published | Not published |
| Website | clear.ml | metaflow.org |
| On ml experiment tracking software | #2 of 39 | #1 of 39 |
ClearML: what it does well
- Manages GPUs across on-premises, cloud, and hybrid setups.
- Provides model development, training, testing, and deployment tools.
- Includes integrations for popular ML frameworks and tools.
- Supports several cloud and S3-compatible storage services.
- Community plan is free.
What to know first
- Pro adds usage charges beyond its per-user price.
- Scale and Enterprise pricing require a custom quote.
- Self-hosted security setup calls for restricting ports and configuring login authentication.
Metaflow: what it does well
- Automatically tracks flows, experiments, and artifacts.
- Supports local workflow construction and testing.
- Can scale compute using cloud accounts or Kubernetes.
- Offers several cloud and workflow integrations.
What to know first
- Local-only setup lacks external compute scaling.
- Local-only setup is not for production-grade deployments.
- The Python package installation page lists macOS and Linux.
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