| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Linux | — | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 0 |
| Spec score · ML Experiment Tracking Software | 7.8 (#10) | 7.7 (#12) |
| Experiment tracking | Logged data is stored in a dvclive directory and tracked as a DVC experiment for analysis and comparison. | The platform tracks metrics and experiment details including hyperparameters and Git commits. |
| Founded | 2018 | 2020 |
| Framework integrations | The supported ML frameworks listed include Fast.ai, Hugging Face, Keras, LightGBM, MMCV, Optuna, PyTorch, PyTorch Lightning, Scikit-learn, TensorFlow, XGBoost, and Ultralytics YOLO v8. | LabML documentation lists sample integrations for FastAI, Keras, and PyTorch Lightning. |
| Purpose | DVCLive is a Python API module for logging machine learning parameters, metrics, artifacts, images, and plots. | LabML is an open-source platform for monitoring deep learning experiments and hardware usage. |
| Support | DVC directs users to its Discord community, GitHub issues, and forum for help and feedback. | The LabML app page lists contact email [email protected]. |
