Keywords AI
LangSmith vs Lunary
Compare LangSmith and Lunary 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 | LangChain developers who need integrated tracing, evaluation, and prompt management | — |
| Website | smith.langchain.com | lunary.ai |
| Key Features |
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| Use Cases |
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When to Choose LangSmith vs Lunary
- Debugging LangChain and LangGraph applications
- Prompt iteration and A/B testing
- LLM output evaluation and scoring
About LangSmith
LangSmith is LangChain's observability and evaluation platform for LLM applications. It provides detailed tracing of every LLM call, chain execution, and agent step—showing inputs, outputs, latency, token usage, and cost. LangSmith includes annotation queues for human feedback, dataset management for evaluation, and regression testing for prompt changes. It's the most comprehensive debugging tool for LangChain-based applications.
About Lunary
Lunary is an open-source LLM observability platform for monitoring AI applications in production. It provides request tracing, cost tracking, user analytics, and prompt management with a clean dashboard. Lunary can be self-hosted for data privacy and offers a managed cloud option.
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.
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