Keywords AI
LangSmith vs Portkey
Compare LangSmith and Portkey 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 | portkey.ai |
| Key Features |
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| Use Cases |
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When to Choose LangSmith vs Portkey
- 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 Portkey
Portkey provides LLM observability alongside its gateway capabilities, offering detailed logging, metrics, and tracing for LLM API calls. Teams can monitor latency, costs, token usage, and error rates across providers, with request-level debugging and analytics dashboards for production AI applications.
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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