Traceloop vs Weights & Biases: Observability, Prompts & Evals Comparison
Compare Traceloop and Weights & Biases side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 9, 2026
The short answer
Choose Traceloop if acquired by ServiceNow for $60-80M providing strong financial backing and integration opportunities.
Choose Weights & Biases if free tier for personal projects and academic research provides excellent value.
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Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | open-source | Freemium |
| Best For | Teams already using Datadog/Splunk wanting LLM observability | ML engineers and researchers who need comprehensive experiment tracking |
| Website | traceloop.com | wandb.ai |
| Key Features |
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| Use Cases | — |
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Pros & Cons: Traceloop vs Weights & Biases
- +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
- −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
- +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
- −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
Pricing: Traceloop vs Weights & Biases
- · Personal projects
- · Limited storage
- · Community support
- · Core features
- · Full product features
- · Enhanced storage
- · Email support
- · Team collaboration
- · For academic research
- · Unlimited tracked hours
- · 200GB cloud storage
- · Up to 100 seats
- · Custom pricing
- · Advanced features
- · Dedicated support
- · SLA guarantees
When to Choose Traceloop vs Weights & Biases
- ML experiment tracking and comparison
- Model training run management
- Team collaboration on ML projects
About Traceloop
Traceloop is an observability and quality assurance platform designed to help teams ship LLM applications 10x faster by transforming evaluation data into continuous feedback loops. The platform enables developers to monitor, test, and improve large language model applications throughout their lifecycle. Built on OpenTelemetry and shipping with OpenLLMetry (their open-source SDK), Traceloop provides real-time monitoring with just one line of code, giving live visibility into prompts, responses, latency, and more. The platform offers built-in quality evaluations for faithfulness, relevance, and safety that automatically apply to production data, along with custom evaluators that users can define and train on annotated examples. Traceloop features automated quality gates that run evaluations automatically on pull requests and in real-time during app execution, plus LLM drift detection to catch performance degradation before it reaches users. The platform supports 20+ LLM providers including OpenAI, Anthropic, Gemini, Bedrock, and Ollama, and integrates with popular frameworks like LangChain, LlamaIndex, and CrewAI. In March 2026, Traceloop was acquired by ServiceNow for $60-80 million, marking the third Israeli acquisition by ServiceNow in under three months. The platform is SOC 2 and HIPAA compliant with cloud, on-premises, and air-gapped deployment options. Traceloop has been recognized as a Gartner Cool Vendor and serves notable clients including HiBob, Target, Miro, IBM, and Babbel.
About Weights & Biases
Weights and Biases (W and B) is a machine learning operations platform founded in 2017 by Chris Van Pelt, Lukas Biewald, and Shawn Lewis in San Francisco, California. The platform offers performance visualization tools for machine learning, helping companies track models, visualize performance, and automate training and model improvement workflows. W and B provides comprehensive experiment tracking, model versioning, and collaborative tools for ML teams. In March 2025, Weights and Biases was acquired by CoreWeave, strengthening its position in the AI infrastructure ecosystem. The company raised a total of USD 250M from investors including CoreWeave, Coatue, Bloomberg Beta, and Insight Partners. W and B offers a free tier for personal projects and provides academic institutions with free Pro licenses for non-profit research, including unlimited tracked hours, 200GB cloud storage, up to 25GB/month of Weave data ingestion, and up to 100 seats. Paid plans start at USD 60/month with additional cloud storage available at USD 0.03 per GB.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evalstools →Other Observability, Prompts & Evals Tools
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