Side by side
LabML vs Lamin
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 AndroidAPIiPhone+3
LabML combines experiment tracking, live hardware monitoring, run comparison, and reproducibility details across several access options. Its related PyTorch implementations add practical reference material for common deep learning topics.
Visit LabML Free plan APISelf-hostedWeb
Choose Lamin for R&D data management that combines lineage, records, dataset governance, and documented integrations. Its free plan is limited to open assets and public queries; hosted databases and storage are part of paid plans.
Visit LaminThe facts
| LabML | Lamin | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Android, API, iPhone, Linux, Self-hosted, Web | API, Self-hosted, Web |
| Lowest paid plan | Not published | Pro: $20 a month |
| Plans published | None | 4 |
| Maker | Not published | Not published |
| Website | labml.ai | lamin.ai |
| On ml experiment tracking software | #10 of 39 | #6 of 39 |
LabML: what it does well
- Free and open-source
- Real-time experiment and hardware monitoring
- Tracks hyperparameters and Git commits
- Compares results across multiple runs
- Supports distributed training across machines
What to know first
- Self-hosted server requires MongoDB
- MIT License provides no warranty
Lamin: what it does well
- Tracks data, code, and agent activity across workflows.
- Supports schema-based LIMS and ELN records.
- Enables dataset validation, annotation, branching, and versioning.
- Offers web, API, and self-hosted platforms.
- Documents integrations with research and coding tools.
What to know first
- Pro hosted storage and egress have additional usage charges.
- Team and Enterprise pricing is per seat and billed annually.