LangSmith vs Arize Phoenix
Detailed side-by-side comparison to help you choose the right tool
LangSmith
🔴DeveloperAI Observability
LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.
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FreeArize Phoenix
🔴DeveloperAI Observability
Arize Phoenix is an open-source AI observability and evaluation platform for tracing, testing, and improving LLM applications and agents.
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FreeFeature Comparison
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💡 Our Take
Choose LangSmith for managed SaaS convenience, integrated prompt hub, and first-class LangChain support. Choose Arize Phoenix if you want a fully open-source, self-hostable observability tool with strong focus on RAG evaluation and embedding-space analysis, especially if you already use Arize's broader ML observability platform.
LangSmith - Pros & Cons
Pros
- ✓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.
Cons
- ✗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.
Arize Phoenix - Pros & Cons
Pros
- ✓Open-source Phoenix can run locally or on controlled infrastructure without a software license fee.
- ✓OpenTelemetry tracing reduces instrumentation lock-in.
- ✓Datasets, experiments, evaluations, and Prompt IDE connect evidence to changes.
- ✓AX Free and Pro include unlimited users and evaluations at published prices.
Cons
- ✗Self-hosting shifts upgrades, storage, access control, backups, and availability to the user's team.
- ✗Agent runs can generate many spans, consuming 25,000 or 50,000 allowances quickly.
- ✗Managed retention of 15 or 30 days may be short for audits or long incident cycles.
- ✗Fetched pages did not explicitly document native MCP support.
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