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TensorBoard vs Trackio

TensorBoard

tensorflow.org

Trackio

huggingface.co

Side by side

FigureTensorBoardTrackio
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
WebYesYes
WindowsYesYes
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published11
Spec score · Experiment Tracking7.6 (#7)7.4 (#11)
Spec score · ML Experiment Tracking Software7.6 (#16)7.4 (#20)
PurposeTensorBoard is a suite of visualization tools for understanding, debugging, and optimizing TensorFlow programs during machine learning experimentation.Trackio is a lightweight Python library for tracking machine learning experiments, built on Hugging Face Buckets and Spaces.

Plans

TensorBoard

  • TensorBoardFree

TensorBoard pricing →

Trackio

  • FreeFree

Trackio pricing →

In their own words

TensorBoard

TensorBoard is a free suite of visualization tools for understanding, debugging and optimizing TensorFlow programs during machine-learning experiments. It tracks metrics such as loss and accuracy, and its Graph Explorer displays model graphs for inspection. Dashboards show changes in tensor distributions through histograms and percentile summaries. The tools can also display logged images, audio and text, project high-dimensional embeddings and profile TensorFlow programs. In Keras workflows, a TensorFlow callback records metrics, training graph visualizations, weight histograms and sampled profiling data. TensorBoard can be launched from the command line or in notebooks using the `%tensorboard` line magic. It is designed for offline use, including local environments, corporate firewalls and datacenters. Version 2.0 and later defaults to `--host localhost`; `--bind_all` serves it on the public network over IPv4 and IPv6. Without a TensorFlow installation, it does not support log directories on Google Cloud Storage. The README identifies Chrome and Firefox as supported browsers and warns that others may have bugs or performance issues.

Visit tensorflow.org

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.

Visit huggingface.co