Machine Learning · head to head
ClearML vs Weka
ClearML
Machine Learning
Open-source MLOps platform for experiment tracking and orchestration
- From
- Free
- Rated
- -
The short version
- Each has a real cost: ClearML broad scope means more to learn and more to run than a focused tracking tool; 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: ClearML covers Experiment tracking, Weka covers Classification.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which ClearML and Weka actually diverge.
Identical on both: starting price (Free), 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 ClearML
- Experiment tracking
- Remote execution
- Data versioning
- Pipelines
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.
ClearML
- Tracking experiments across a team so results are reproduciblenot Weka
- Moving training from laptops to shared GPU hardware without repackagingnot Weka
- Versioning datasets alongside the experiments that consumed themnot Weka
Weka
- Teaching and exploring classic machine learning algorithms through a GUInot ClearML
- Running data mining experiments and preprocessing without writing codenot ClearML
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
ClearML
- Broad scope means more to learn and more to run than a focused tracking tool
- Self-hosting the server is real infrastructure — database, file storage and web server
- Documentation quality is uneven across the newer parts of the platform
- Smaller community than the most popular tracking tools, so fewer worked examples exist
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
ClearML
Free- Open sourceFree
- Experiment tracking
- Pipelines
- Self-hosted server
Weka
Free- Open SourceFree
- All ML algorithms
- GUI and CLI
- Java API
Which should you pick?
Choose ClearML if
- You need experiment tracking.
- You want to start without paying.
- You work on Linux, macOS, Windows, Docker, Kubernetes.
- You also want remote execution.
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 ClearML or Weka better?
- Neither clearly leads. ClearML 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, ClearML or Weka?
- ClearML starts at Free and Weka at Free.
- Does ClearML or Weka run on more platforms?
- ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Weka runs on Linux, Mac, Windows.
- Can I use ClearML for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is ClearML best used for?
- ClearML is most often used for tracking experiments across a team so results are reproducible, moving training from laptops to shared gpu hardware without repackaging, versioning datasets alongside the experiments that consumed them. Of those, tracking experiments across a team so results are reproducible and moving training from laptops to shared gpu hardware without repackaging are not what Weka is typically brought in for.
- What can ClearML do that Weka cannot?
- ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Weka covers Classification, Regression, Clustering, Association rules.
Answered from the vendors’ own pages
ClearML: Is ClearML free?
The open-source version is free and self-hostable. Hosted and enterprise tiers are paid.
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.
SourceClearML: How much code does tracking require?
Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.
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.
SourceClearML: Does ClearML replace MLflow?
It covers MLflow’s tracking and adds orchestration, remote execution and data versioning. Whether that breadth is an advantage or extra weight depends on whether you need the rest.
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.
SourceWeka: 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.
SourceRelated pages
Other head to heads
- ClearML vs MLflow
- ClearML vs Weights & Biases
- ClearML vs Comet ML
- ClearML vs Neptune.ai
- ClearML vs Dataiku
- ClearML vs Pachyderm
- ClearML vs Azure Machine Learning
- ClearML vs Domino Data Lab
- ClearML vs DVC
- ClearML vs AWS SageMaker
- ClearML vs Google Vertex AI
- ClearML vs DataRobot
- ClearML vs Pinecone
- ClearML vs Python
- ClearML vs PyTorch
- ClearML vs scikit-learn
- ClearML vs Apache Spark MLlib
- ClearML vs Weaviate
- ClearML vs Orange
- ClearML vs Databricks
- ClearML vs MATLAB
- ClearML vs SAS
- ClearML vs Minitab
- ClearML vs Mistral AI
- ClearML vs Ollama
- ClearML vs OpenRouter
- ClearML vs BigQuery ML
- ClearML vs JMP
- Weka vs MLflow
- Weka vs Weights & Biases
- Weka vs Comet ML
- Weka vs Neptune.ai
- Weka vs Dataiku
- Weka vs Pachyderm
- Weka vs Azure Machine Learning
- Weka vs Domino Data Lab
- Weka vs DVC
- Weka vs AWS SageMaker
- Weka vs Google Vertex AI
- Weka vs DataRobot
- Weka vs Pinecone
- Weka vs Python
- Weka vs PyTorch
- Weka vs scikit-learn
- Weka vs Apache Spark MLlib
- Weka vs Weaviate
- Weka vs Orange
- Weka vs Databricks
- Weka vs MATLAB
- Weka vs SAS
- Weka vs Minitab
- Weka vs Mistral AI
- Weka vs Ollama
- Weka vs OpenRouter
- Weka vs BigQuery ML
- Weka vs JMP