Side by side
LabML vs TensorBoard
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 APILinuxMac+3
TensorBoard offers a range of visualizations and profiling tools for TensorFlow experimentation at no cost. Consider its browser and storage limitations, and note that `--bind_all` exposes the service on the public network.
Visit TensorBoardThe facts
| LabML | TensorBoard | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Android, API, iPhone, Linux, Self-hosted, Web | API, Linux, Mac, Self-hosted, Web, Windows |
| Lowest paid plan | Not published | Free or on request |
| Plans published | None | 1 |
| Maker | Not published | Not published |
| Website | labml.ai | tensorflow.org |
| On ml experiment tracking software | #10 of 39 | #14 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
TensorBoard: what it does well
- Tracks metrics such as loss and accuracy.
- Graph Explorer displays TensorFlow model graphs.
- Shows histograms and percentile summaries over time.
- Supports logged images, audio, text, and embeddings.
- Designed to run offline.
What to know first
- Without TensorFlow installed, it does not support log directories on Google Cloud Storage.
- Other browsers may have bugs or performance issues.
- `--bind_all` serves on the public network.
Alternatives to LabML Alternatives to TensorBoard The whole list