Machine Learning · head to head
Orange vs Weights & Biases

Weights & Biases
Machine Learning
Developer tools for machine learning
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Orange orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL; Weights & Biases pricing can be prohibitive for large teams without enterprise discounts
- They diverge on capability: Orange covers Visual programming, Weights & Biases covers Experiment tracking.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Orange and Weights & Biases actually diverge.
| Attribute | Orange | Weights & Biases |
|---|---|---|
| Pricing model | open-source | Unknown |
| Platforms | Linux, Mac, Windows | Web, Python SDK, REST API |
| Founded | 1996 | 2017 |
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 Orange
- Visual programming
- Data visualization
- Machine learning
- Text mining
- Bioinformatics
- Python
- scikit-learn
- PyQt
Only in Weights & Biases
- Experiment tracking
- Dataset versioning
- Model registry
- Hyperparameter sweeps
- Collaborative dashboards
- PyTorch
- TensorFlow
- Keras
Both cover
- Linux support
- Mac support
- Windows support
What people use each for
The jobs each tool is most often brought in to do.
Orange
- Visual programming for data mining and machine learning workflowsnot Weights & Biases
- Teaching data science without writing codenot Weights & Biases
- Exploratory data visualisation and clustering on tabular datanot Weights & Biases
Weights & Biases
- Machine learningnot Orange
- Data analysisnot Orange
- Model trainingnot Orange
- Predictive analyticsnot Orange
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Orange
- Orange is licensed under the GNU General Public License version 3, so distributing modified or derived software requires releasing the source under the GPL
- The widgets and canvas are built on Qt, which is itself distributed under GPL 3.0
- Orange add-ons may carry additional licensing requirements set in their own licence files
- Documentation and website content are under Creative Commons Attribution-ShareAlike, which imposes an attribution and share-alike obligation on reuse
- The software is distributed without any warranty of merchantability or fitness for a particular purpose
Weights & Biases
- Pricing can be prohibitive for large teams without enterprise discounts
- Limited integrations compared to some competitors
- Dashboard customization options limited on lower plans
- Requires some setup and configuration knowledge
Pricing, plan by plan
Orange
Free- Open SourceFree
- Visual programming
- Machine learning
- Data visualization
Weights & Biases
Free- FreeFree
- 5 model seats
- 5 GB storage
- 1 GB/month Weave ingestion
- Pro$60/month
- 10 seats
- 100 GB storage
- Private projects
- Teams$179/month
- Team collaboration
- Advanced analytics
- Dedicated support
Which should you pick?
Choose Orange if
- You need visual programming.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want data visualization.
Choose Weights & Biases if
- You need experiment tracking.
- You want to start without paying.
- You work on Web, Python SDK, REST API.
- You also want dataset versioning.
Questions people ask
- Is Orange or Weights & Biases better?
- Neither clearly leads. Orange starts at Free and Weights & Biases at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Orange or Weights & Biases?
- Orange starts at Free and Weights & Biases at Free.
- Does Orange or Weights & Biases run on more platforms?
- Orange runs on Linux, Mac, Windows. Weights & Biases runs on Web, Python SDK, REST API.
- Can I use Orange for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Orange best used for?
- Orange is most often used for visual programming for data mining and machine learning workflows, teaching data science without writing code, exploratory data visualisation and clustering on tabular data. Of those, visual programming for data mining and machine learning workflows and teaching data science without writing code are not what Weights & Biases is typically brought in for.
- What can Orange do that Weights & Biases cannot?
- Orange covers Visual programming, Data visualization, Machine learning, Text mining. Weights & Biases covers Experiment tracking, Dataset versioning, Model registry, Hyperparameter sweeps. Both handle Linux support, Mac support, Windows support.
Answered from the vendors’ own pages
Orange: What is the cost of Orange Data Mining?
Orange Data Mining is free open-source software available for Windows, Mac, and other platforms. There are no subscription fees, licensing costs, or paid tiers.
SourceWeights & Biases: Does Weights & Biases have a free plan?
Yes. The Free tier includes 5 model seats, 5 GB storage, and 1 GB/month Weave ingestion. Academic users get unlimited tracked hours, 200 GB storage, and 100 seats at no cost.
SourceOrange: How is Orange Data Mining funded?
Orange Data Mining is supported through optional voluntary donations. The project encourages donations from users who value the software to support bug fixes, new features, educational content, and infrastructure maintenance.
SourceWeights & Biases: What are the paid plans for Weights & Biases?
Pro starts at $60/month with 10 seats and 100 GB storage. Team plans start at $179/month. Enterprise pricing is custom.
SourceWeights & Biases: What machine learning features does W&B provide?
Weights & Biases captures hyperparameters, metrics, and model outputs automatically. Features include experiment tracking, interactive Reports for sharing findings, Artifacts for managing datasets and models, advanced hyperparameter sweeps, and model deployment tools.
SourceRelated pages
More on Weights & Biases
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- Weights & Biases vs Google Vertex AI
- Weights & Biases vs DataRobot
- Weights & Biases vs AWS SageMaker
- Weights & Biases vs Azure Machine Learning
- Weights & Biases vs Weka
- Weights & Biases vs MATLAB
- Weights & Biases vs KNIME
- Weights & Biases vs Jupyter
- Weights & Biases vs Alteryx
- Weights & Biases vs JMP
- Weights & Biases vs RapidMiner
- Weights & Biases vs Dask
- Weights & Biases vs Fal AI
- Weights & Biases vs Groq
- Weights & Biases vs Haystack
- Weights & Biases vs IBM SPSS
- Weights & Biases vs Neptune.ai
- Weights & Biases vs Comet ML
- Weights & Biases vs MLflow
- Weights & Biases vs ClearML
- Weights & Biases vs Dataiku
- Weights & Biases vs Domino Data Lab
- Weights & Biases vs DVC
- Weights & Biases vs Pachyderm
- Weights & Biases vs Seldon
- Weights & Biases vs Stata
- Weights & Biases vs TensorBoard
- Weights & Biases vs SAS

