LangSmith vs MLflow: Observability, Prompts & Evals Comparison

Compare LangSmith and MLflow side by side. Both are tools in the Observability, Prompts & Evals category.

Quick Comparison

	LangSmith	MLflow
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Freemium	Open Source
Best For	LangChain developers who need integrated tracing, evaluation, and prompt management	ML engineers and AI teams, especially those in the Databricks ecosystem
Website	smith.langchain.com	mlflow.org
Key Features	Trace visualization for LLM chains Prompt versioning and management Evaluation and testing suite Dataset management Tight LangChain integration	OpenTelemetry-native tracing 50+ built-in eval metrics & LLM judges Prompt versioning & management Built-in AI gateway Full MLOps lifecycle (experiments, model registry, deployment)
Use Cases	Debugging LangChain and LangGraph applications Prompt iteration and A/B testing LLM output evaluation and scoring Team collaboration on prompt engineering Regression testing for LLM apps	LLM observability & tracing Automated evaluation Prompt optimization Model deployment Production monitoring

When to Choose LangSmith vs MLflow

Choose LangSmith if you need

Debugging LangChain and LangGraph applications
Prompt iteration and A/B testing
LLM output evaluation and scoring

Pricing: Freemium

Choose MLflow if you need

LLM observability & tracing
Automated evaluation
Prompt optimization

Pricing: Open Source

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.

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About MLflow

Open-source MLOps platform with comprehensive GenAI tracing, evaluation, prompt management, and AI gateway. Maintained by the Linux Foundation.

View MLflow profile →Visit website

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 →

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Quick Comparison

	LangSmith	MLflow
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Freemium	Open Source
Best For	LangChain developers who need integrated tracing, evaluation, and prompt management	ML engineers and AI teams, especially those in the Databricks ecosystem
Website	smith.langchain.com	mlflow.org
Key Features	Trace visualization for LLM chains Prompt versioning and management Evaluation and testing suite Dataset management Tight LangChain integration	OpenTelemetry-native tracing 50+ built-in eval metrics & LLM judges Prompt versioning & management Built-in AI gateway Full MLOps lifecycle (experiments, model registry, deployment)
Use Cases	Debugging LangChain and LangGraph applications Prompt iteration and A/B testing LLM output evaluation and scoring Team collaboration on prompt engineering Regression testing for LLM apps	LLM observability & tracing Automated evaluation Prompt optimization Model deployment Production monitoring

About LangSmith

What is Observability, Prompts & Evals?

Browse all Observability, Prompts & Evals tools →