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LLM Observability
Methodology

Langfuse vs LangSmith

LangfuseLALangfusevsLangSmithLALangSmith
LangfuseLangSmith
35%
65%

Leading: LangSmith (65.3%)

Statistics

MetricValue
Langfuse wins279
LangSmith wins525
Abstains (no tool)22
Other tool chosen183
Decisive cases804
Langfuse win rate (unweighted)34.7%
95% CI31.5% - 38.1%
Langfuse win rate (weighted)34.7%

Comments

Langfuse

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LangSmith

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Per-model breakdown

ModelTierLangfuseLangSmithNoneOtherA rate
GPT 5.4Frontier5130094%
GPT 5.3 CodexFrontier4860089%
Claude Opus 4.6Frontier4770087%
Claude Sonnet 4.6Frontier17370031%
GLM 5 TurboFrontier450007%
MiMo V2 ProFrontier153002%
DeepSeek V3.2Mid349026%
GPT 5.4 MiniMid10411220%
Gemini 2.5 ProFrontier149402%
Claude Haiku 4.5Small34140671%
DeepSeek R1 0528Frontier048150%
Kimi K2.5Frontier24231051%
Qwen3 Coder NextMid21241847%
Mistral Small 4Mid243074%
MiniMax M2.7Frontier1401112%
Llama 4 MaverickFrontier42802213%
Llama 4 ScoutSmall110535100%
Devstral 2 2512Mid098330%
Gemini 2.5 FlashSmall010520%

Per-prompt breakdown

PromptTierLangfuseLangSmithNoneOtherA rate
ai-support-agent-platformIntermediate3410712924%
ai-support-agent-platformAdvanced498603636%
ai-revenue-ops-copilotIntermediate379802927%
ai-support-agent-platformBeginner647053048%
ai-revenue-ops-copilotAdvanced448613334%
ai-revenue-ops-copilotBeginner5178152640%