ClearML vs Trackio
ClearML
clear.mlTrackio
huggingface.coSide by side
| Figure | ClearML | Trackio |
|---|---|---|
| Price from | $15/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · ML Experiment Tracking Software | 8.7 (#3) | 7.4 (#20) |
| Spec score · Experiment Tracking | 8.7 (#3) | 7.4 (#11) |
| Integrations | The integrations documentation lists PyTorch, TensorFlow, Keras, scikit-learn, XGBoost, LightGBM, Optuna, Hydra, TensorBoard, Matplotlib, and LangChain among supported integrations. | Trackio documents native integrations with Transformers and TRL, plus a RapidFire AI integration for fine-tuning and RAG experiments. |
Plans
ClearML
- CommunityFree
- Pro$15 a month
- EnterprisePriced on request
- ScalePriced on request
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.
Trackio
Trackio is a free Python library for recording and comparing machine-learning experiments, built on Hugging Face Buckets and Spaces. Its API follows the wandb.init, wandb.log, and wandb.finish patterns and is documented as a drop-in replacement for compatible workflows. A dashboard runs locally by default, while logs can be stored locally, in a Hugging Face Bucket, or on a self-hosted server. Runs record metrics and configuration, and the dashboard groups them for comparison. Logging can include tables, Markdown reports, images, video, audio, 3D objects, HTML, and Matplotlib or Plotly figures. Optional packages enable NVIDIA GPU or Apple Silicon monitoring. Trackio documents integrations with Transformers and TRL, plus RapidFire AI for fine-tuning and RAG experiments. Alerts can be printed, stored, queried, shown in the dashboard, or sent through Slack and Discord webhooks. The dashboard can also run as an HTTP API and MCP server; mutation tools are gated by a write token. For self-hosted servers outside Hugging Face Spaces, ingestion and uploads require a write token that the documentation says to keep secret on untrusted networks. Trackio has no first-class hyperparameter sweep API; its docs describe using Python loops with one run per configuration.