Machine Learning · head to head
TensorBoard vs Weka
TensorBoard
Machine Learning
Local visualisation for training runs, reading event files written to a directory
- From
- Free
- Rated
- -
The short version
- Each has a real cost: TensorBoard there is no authentication of any kind, so putting it on a shared host exposes every run, every metric and every logged sample image to anyone who can reach the port, and adding access control means building and maintaining a reverse proxy.; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- They diverge on capability: TensorBoard covers Scalar dashboards, Weka covers Classification.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which TensorBoard and Weka actually diverge.
| Attribute | TensorBoard | Weka |
|---|---|---|
| Platforms | Web | Linux, Mac, Windows |
| Founded | Unknown | 1993 |
Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated), category (Machine Learning).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in TensorBoard
- Scalar dashboards
- Run comparison
- Graph visualisation
- Histograms and distributions
- Embedding projector
- Image, audio and text panels
- Hyperparameter view
- Profiler
Only in Weka
- Classification
- Regression
- Clustering
- Association rules
- Feature selection
- Java
- R
- Python
What people use each for
The jobs each tool is most often brought in to do.
TensorBoard
- Watching a training run in progress on a workstation or a remote box, to decide whether to stop it earlynot Weka
- Diagnosing why a model is not learning, by looking at gradient and weight histograms rather than only the loss curvenot Weka
- Profiling a slow training loop to find out whether the bottleneck is the data pipeline or the acceleratornot Weka
- Working in an environment with no outbound network access, where a hosted tracking service is not an optionnot Weka
Weka
- Teaching and exploring classic machine learning algorithms through a GUInot TensorBoard
- Running data mining experiments and preprocessing without writing codenot TensorBoard
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
TensorBoard
- There is no authentication of any kind, so putting it on a shared host exposes every run, every metric and every logged sample image to anyone who can reach the port, and adding access control means building and maintaining a reverse proxy.
- Event files grow without limit and the interface loads runs into memory, so a directory holding hundreds of runs or a script logging scalars every step becomes slow to start and unpleasant to navigate well before the disk fills.
- It shows only what the training loop chose to write, so nothing connects a curve back to the code commit, the data set version or the environment unless the engineer logged those explicitly, which means the reproducibility problem is left entirely to you.
- TensorBoard.dev, the hosted service for sharing a run by link, was shut down at the end of 2023, so results now travel between colleagues as screenshots or through a deployment somebody on the team has to operate.
- Comparing runs is done by ticking boxes in a run list, which is fine for ten runs and useless for a thousand, and that threshold is precisely where teams start paying for MLflow, Weights and Biases or Neptune instead.
Weka
- The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
- Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
- Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture
Pricing, plan by plan
TensorBoard
FreeNo published plan breakdown. See the TensorBoard review.
Weka
Free- Open SourceFree
- All ML algorithms
- GUI and CLI
- Java API
Which should you pick?
Choose TensorBoard if
- You need scalar dashboards.
- You want to start without paying.
- You also want run comparison.
Choose Weka if
- You need classification.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want regression.
Questions people ask
- Is TensorBoard or Weka better?
- Neither clearly leads. TensorBoard starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, TensorBoard or Weka?
- TensorBoard starts at Free and Weka at Free.
- Does TensorBoard or Weka run on more platforms?
- TensorBoard runs on Web. Weka runs on Linux, Mac, Windows.
- Can I use TensorBoard for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is TensorBoard best used for?
- TensorBoard is most often used for watching a training run in progress on a workstation or a remote box, to decide whether to stop it early, diagnosing why a model is not learning, by looking at gradient and weight histograms rather than only the loss curve, profiling a slow training loop to find out whether the bottleneck is the data pipeline or the accelerator, working in an environment with no outbound network access, where a hosted tracking service is not an option. Of those, watching a training run in progress on a workstation or a remote box, to decide whether to stop it early and diagnosing why a model is not learning, by looking at gradient and weight histograms rather than only the loss curve are not what Weka is typically brought in for.
- What can TensorBoard do that Weka cannot?
- TensorBoard covers Scalar dashboards, Run comparison, Graph visualisation, Histograms and distributions. Weka covers Classification, Regression, Clustering, Association rules.
Answered from the vendors’ own pages
TensorBoard: Does it work with PyTorch?
Yes. PyTorch includes a SummaryWriter that emits the same event file format, and Lightning wires it up by default. Nothing about the tool requires TensorFlow at run time.
Weka: What is the cost of Weka software?
Weka is provided at no cost as open-source software released under the GNU General Public License, making it freely available for download and use.
SourceTensorBoard: Do I have to install TensorFlow to use it?
No. The tensorboard package installs on its own. Some plugins expect TensorFlow to be present, but the scalar, histogram and image dashboards do not.
Weka: Are there commercial licensing options available?
Yes, the project offers information about commercial licenses for organizations requiring non-GPL terms, which can be found in their commercial applications documentation.
SourceTensorBoard: Is it an experiment tracker?
No, and treating it as one is the common mistake. It visualises whatever a run wrote to disk. It does not store hyperparameters, code versions, artefacts or results in a way that survives someone deleting the log directory.
Weka: What support resources are available to users?
Multiple support avenues exist including comprehensive documentation, frequently asked questions, dedicated help resources, and access to courses for learning the platform.
SourceTensorBoard: How do I share a dashboard with a colleague?
Host it yourself behind your own authentication, or send screenshots. The hosted sharing service was retired at the end of 2023.
Weka: Is source code access provided?
Yes, developers have full access to source code through the Git repository, along with development documentation and code credits for contributors.
SourceTensorBoard: What does it cost?
Nothing. It is Apache 2.0 licensed and runs on your own machine.
Related pages
More on TensorBoard
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