Traceloop vs Weights & Biases (2026)
Updated March 9, 2026
Overview
The OpenTelemetry standard for AI. Pipes LLM telemetry into Datadog, Splunk, or any OTel backend.
Weights & Biases (W&B) is the leading experiment tracking and ML operations platform, now extended to LLM applications. W&B Traces provides observability for LLM pipelines, while W&B Weave offers evaluation and production monitoring. The platform also supports model training tracking, hyperparameter sweeps, and artifact management, making it a comprehensive MLOps solution.
Key features
Core capabilities each platform advertises.
- OpenTelemetry
- OpenLLMetry
- Vendor-neutral
- OTel integration
- ML experiment tracking
- Model and dataset versioning
- Collaborative dashboards
- Sweeps for hyperparameter tuning
- Prompt monitoring and evaluation
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Acquired by ServiceNow for $60-80M providing strong financial backing and integration opportunities
- Built on OpenTelemetry standards with open-source OpenLLMetry SDK
- Recognized as Gartner Cool Vendor demonstrating industry validation
- One-line code integration for quick setup and deployment
- Enterprise-ready with SOC 2, HIPAA compliance and multiple deployment options
Cons
- ServiceNow acquisition may lead to platform changes, pricing adjustments, or strategic shifts
- Small team of 9 employees may be absorbed into larger ServiceNow organization affecting support
- Limited transparent pricing information following acquisition
- Uncertainty around long-term product roadmap under new ownership
Pros
- Free tier for personal projects and academic research provides excellent value
- Comprehensive experiment tracking and model versioning capabilities
- Strong visualization tools help teams understand model performance
- Acquisition by CoreWeave provides infrastructure synergies and stability
Cons
- Pricing can become expensive for large teams and enterprises
- Additional storage costs can add up quickly for data-intensive workflows
- Learning curve for advanced features may slow initial adoption
- Platform complexity may be overkill for simple ML projects
Traceloop or Weights & — which should you choose?
Choose Traceloop if you wantChoose if you want
Choose Weights & if you wantChoose if you want
- ML experiment tracking and comparison
- Model training run management
- Team collaboration on ML projects
- Hyperparameter optimization
- Model registry and versioning
Compare Traceloop and Weights & Biases on your own traffic
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