Head-to-head · ML Experiment Tracking Software
Trackio vs LUML Flow
Trackio leads on 0 checks, LUML Flow on 0, and 6 are even. Who comes out ahead on the 6 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreTrackio · 7.7/10
- Free planboth
Trackio scores higher on our rubric for ml experiment tracking software: 7.7 against 7.0 out of 10; our editors rank them #12 and #19.
Trackio is the better fit for free teams using Hugging Face tooling. LUML Flow is the better fit for open-source teams tracking ML and LLM experiments.
- Trackio fits best
Free teams using Hugging Face tooling
- LUML Flow fits best
Open-source teams tracking ML and LLM experiments
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Side by side
| Feature | Trackio 7.7/10 Visit ↗ | LUML Flow 7.0/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 7.7 | 7.0 |
| Ranking | #12 in ML Experiment Tracking Software | #19 in ML Experiment Tracking Software |
| Best for | Free teams using Hugging Face tooling | Open-source teams tracking ML and LLM experiments |
| Pricing model | Free | Free plan + paid |
| Starting price | Free plan | — |
| Free plan | ✓ | ✓ |
| Free trial | — | — |
| Deployment | Cloud, Self-hosted | Cloud, Self-hosted |
| Support | Docs | Email, Community, Docs |
| Integrations | 5 integrations | 12 integrations |
| Built for | Solo, Small business, Mid-market | Solo, Small business, Mid-market |
| Features Trackio 5/5 · LUML Flow 5/5 | ||
| Run comparison | ✓ | ✓ |
| Artifact tracking | ✓ | ✓ |
| Dataset versioning | ✓ | ✓ |
| Model registry | ✓ | ✓ |
| API and SDK access | ✓ | ✓ |
| Specs | ||
| Deployment options | Not checked yet | Hybrid |
| Our review | ||
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| Our verdict | Trackio is a free, open-source experiment tracking library for ML developers, researchers, and teams building Python-based training workflows. It records metrics, configurations, media, traces, and versioned artifacts, then presents… Read the review → |
LUML Flow is a local-first experiment tracker for predictive machine learning and generative AI workflows. It records parameters, metrics, model artifacts, traces, evaluation samples, scorers, human annotations, and file attachments while… Read the review → |
Strengths and trade-offs
Trackio — where it wins
- Free tracking with run grouping and side-by-side comparisons
- Versioned artifacts with aliases, lineage, and registries
- Local, Hugging Face Spaces, or self-hosted deployment
Where it doesn't
- Integrations are centered on the Hugging Face ecosystem
- Registry capabilities are under active development
- Primarily designed for Python-based ML workflows
LUML Flow — where it wins
- Tracks parameters, metrics, models, traces, evaluations, and attachments
- Supports comparison, SQLite storage, and a versioned model registry
- Integrates with PyTorch, LangChain, TensorFlow, and other ML tools
Where it doesn't
- Light is limited to 1 user, 1 orbit, 50 artifacts, and 1 satellite
- Pro supports up to 5 users and 1,000 artifacts
- Platform access is centered on API and self-hosted deployment
- Trackio7.7/10 · Free plan
A free tracker for Hugging Face-centered teams that need runs, artifacts, and registries.
Visit TrackioFull verdict → - LUML Flow7.0/10 · Free plan
A local-first tracker with strong ML, LLM, evaluation, and registry coverage.
Visit LUML FlowFull verdict →
All ML experiment tracking software comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update