LangSmith vs PandaProbe

Detailed side-by-side comparison to help you choose the right tool

LangSmith

🔴Developer

AI Observability

LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.

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Starting Price

Free

🔴Developer

AI Observability

Open-source AI agent engineering platform for tracing, evaluating, and debugging agent runs across any framework and LLM provider.

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Starting Price

Free

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Feature	LangSmith	PandaProbe
Category	AI Observability	AI Observability
Pricing Plans	3 listed plans	3 listed plans
Starting Price	Free	Free
Key Features	• Tracing for any LLM stack via Python/TypeScript SDKs or OpenTelemetry • LLM-as-judge, code-based and pairwise evaluations • Versioned prompts with production A/B traffic splits	• One-line instrument() call for full agent execution tracing • Framework-agnostic: Google ADK, LangChain, CrewAI, AutoGen, and more • Works with any LLM provider (OpenAI, Anthropic, Google, Mistral, local)

✓Best-in-class integration if you already use LangChain or LangGraph.
✓Eval suites are practical enough to actually gate releases on, not just dashboards.
✓Self-hosted Enterprise tier covers SOC 2 and regulated environments.

✗Per-trace pricing on Plus surprises teams that scale production traffic quickly.
✗Non-LangChain stacks work but trade ergonomic polish for SDK overhead.
✗Some eval features require additional LLM spend on top of the platform fee.

✓Single instrument() call is genuinely simpler than manual span instrumentation in competitors
✓Framework-agnostic design means no lock-in to a specific agent framework
✓Free Hobby tier with no credit card makes evaluation frictionless
✓Self-hostable option is critical for teams with sensitive data requirements
✓Cost tracking across providers helps optimize model selection
✓Active Product Hunt launch and DevTools recognition signal momentum

✗Very new (May 2026 launch) — limited production track record and community size
✗Pro pricing is contact-based, making cost comparison difficult
✗Smaller ecosystem of integrations and plugins compared to Langfuse or LangSmith
✗Documentation and tutorials are still maturing
✗Missing some advanced features like prompt management that competitors offer
✗Single-person or small team behind the project — sustainability risk

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