ClearML vs Weights & Biases: Which is Better in 2026?
Choosing between ClearML and Weights & Biases comes down to understanding what each tool does best. This comparison breaks down the key differences so you can make an informed decision based on your specific needs, not marketing claims.
Bottom line: Weights & Biases is our overall pick for analytics workflows. Pick ClearML if you need developer tools.
Short on time? Here's the quick answer
We've tested both tools. Here's who should pick what:
ClearML
Open-source MLOps platform for experiment tracking
Best for you if:
- • You need developer tools features specifically
- • ClearML is an open-source MLOps platform for experiment tracking and model management
- • It automates ML pipelines, tracks experiments, and manages model deployment at scale
Weights & Biases
Track, compare, and share ML experiments and models
Best for you if:
- • You need analytics features specifically
- • MLOps platform for experiment tracking
- • Visualize and compare ML training runs
| At a Glance | ||
|---|---|---|
Starts at | FreeFree tier available | FreeFree tier available |
Best For | Developer Tools | Analytics |
Rating | 4.7/5 | 4.7/5 |
Free plan | Yes | Yes |
Choose ClearML or Weights & Biases?
Choose ClearML if
Open-source MLOps platform for experiment tracking
- MLOps platform
- Experiment tracking
- Data management
- Budget matters (Free vs Free)
- Your work is developer tools-shaped, not analytics-shaped
Choose Weights & Biases if
Track, compare, and share ML experiments and models
- Great visualizations
- Team collaboration
- Free tier
- Your work is analytics-shaped, not developer tools-shaped
| Feature | ClearML | Weights & Biases |
|---|---|---|
| Pricing Model | Freemium | Freemium |
| User Rating | ★4.7/5 13 reviews | ★4.7/5 44 reviews |
| Categories | Developer ToolsAnalytics | AnalyticsData Visualization |
In-Depth Analysis
ClearML
Open-source MLOps platform for experiment tracking
Strengths
- +MLOps platform
- +Experiment tracking
- +Data management
- +Open source core
- +Self-hostable
Weaknesses
- -Learning curve
- -UI complex
- -Documentation dense
- -Enterprise expensive
- -Smaller community
Key features
Weights & Biases
Track, compare, and share ML experiments and models
Strengths
- +Great visualizations
- +Team collaboration
- +Free tier
Weaknesses
- -Learning curve
- -Can be slow
Key features
Pricing: ClearML vs Weights & Biases
| Plan | ClearML | Weights & Biases |
|---|---|---|
| Tier 1 | Free Community | Free Free |
| Tier 2 | $15 month per user Pro | $60 Pro |
| Tier 3 | custom Scale | Free Academic |
| Tier 4 | custom Enterprise | Custom Enterprise |
Pricing verified from each vendor's public pricing page. Compare in detail on ClearML pricing and Weights & Biases pricing.
Who Should Use What?
On a budget?
Both are freemium. Compare plans on their websites.
Go with: ClearML
Want the highest-rated option?
ClearML: 4.7/5 (13 reviews). Weights & Biases: 4.7/5 (44 reviews).
Go with: ClearML
Value user reviews?
ClearML: 13 reviews (4.7/5). Weights & Biases: 44 reviews (4.7/5).
Go with: Weights & Biases
3 Questions to Help You Decide
What's your budget?
Both are freemium. Pricing won't help you decide here.
What's your use case?
ClearML is a developer tools tool. Weights & Biases is in analytics. Pick the category that matches your needs.
How important are ratings?
Both are rated 4.7/5.
Key Takeaways
Weights & Biases
- Larger review base (44 reviews)
- Free tier available
- Our pick for this comparison
ClearML
- Better fit for developer tools
The Bottom Line
Weights & Biases is our pick.
Frequently Asked Questions
Is ClearML or Weights & Biases better?
Weights & Biases is rated in our evaluation. Both are freemium.
What are ClearML and Weights & Biases used for?
ClearML: Open-source MLOps platform for experiment tracking. Weights & Biases: Track, compare, and share ML experiments and models.
What does ClearML cost vs Weights & Biases?
ClearML is freemium (free tier + paid plans). Weights & Biases is freemium (free tier + paid plans). Visit their websites for detailed pricing.
