LangSmith vs Sentry: Observability, Prompts & Evals Comparison
Compare LangSmith and Sentry side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose LangSmith if deep integration with LangChain framework provides unmatched observability for LangChain applications.
Choose Sentry if developer-friendly platform.
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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 | sentry.io |
| Key Features |
| — |
| Use Cases |
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Pros & Cons: LangSmith vs Sentry
- +Deep integration with LangChain framework provides unmatched observability for LangChain applications
- +Comprehensive evaluation capabilities with custom metrics and automated regression testing
- +Excellent tracing UI with detailed step-by-step execution visualization
- +Strong dataset management and annotation workflows for human feedback
- −Tight coupling to LangChain ecosystem limits flexibility for non-LangChain applications
- −UI scalability issues reported when working with very large datasets
- −Production testing limitations - relies primarily on production logs for test datasets
- −SaaS-only deployment with no self-hosting option may not suit all enterprise requirements
- +Developer-friendly platform
- +Production-ready
- +Good performance
- +Active development
- −Enterprise pricing varies
- −Setup complexity
- −Learning curve
Pricing: LangSmith vs Sentry
- · 5,000 traces per month
- · 14-day retention
- · One seat
- · Basic evaluations
- · 100,000 traces (overage ~$0.50 per 1,000)
- · 400-day retention
- · Full evaluations
- · Custom dashboards
- · Custom trace volumes
- · Custom retention policies
- · SSO
- · Dedicated support
- · Core features
- · Community support
- · Basic limits
- · Advanced features
- · Higher limits
- · Priority support
- · Custom solutions
- · Dedicated support
- · SLA guarantees
When to Choose LangSmith vs Sentry
- 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 building production-grade LLM applications. Founded in July 2023 by Harrison Chase and Ankush Gola as part of the LangChain ecosystem, LangSmith provides comprehensive tracing of every LLM call, chain execution, and agent step with detailed visibility into inputs, outputs, latency, token usage, and cost. The platform includes annotation queues for human feedback, dataset management for systematic evaluation, and regression testing capabilities for prompt changes. With over 1 million developers using LangChain products globally, LangSmith has become the go-to debugging and monitoring tool for teams building with the LangChain framework, serving major enterprises including Klarna, LinkedIn, Replit, GitLab, Elastic, and Cisco.
About Sentry
Sentry provides error tracking and performance monitoring with AI-powered insights for applications. The platform provides comprehensive features for production AI applications with focus on reliability and developer experience.
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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