Keywords AI
DeepEval vs Weights & Biases
Compare DeepEval and Weights & Biases side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | — | Freemium |
| Best For | — | ML engineers and researchers who need comprehensive experiment tracking |
| Website | deepeval.com | wandb.ai |
| Key Features | — |
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| Use Cases | — |
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When to Choose DeepEval vs Weights & Biases
- ML experiment tracking and comparison
- Model training run management
- Team collaboration on ML projects
About DeepEval
DeepEval is an open-source LLM evaluation framework built for unit testing AI outputs. It provides 14+ evaluation metrics including hallucination detection, answer relevancy, and contextual recall. Integrates with pytest, supports custom metrics, and works with any LLM provider for automated quality assurance in CI/CD pipelines.
About Weights & Biases
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.
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 & Evals tools →