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LLM Evals
Methodology

Humanloop vs LangChain

HUHumanloopvsLALangChain
HumanloopLangChain
40%
60%

Leading: LangChain (59.6%)

Statistics

MetricValue
Humanloop wins46
LangChain wins68
Abstains (no tool)90
Other tool chosen2240
Decisive cases114
Humanloop win rate (unweighted)40.4%
95% CI31.8% - 49.5%
Humanloop win rate (weighted)40.4%

Comments

Humanloop

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LangChain

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Per-model breakdown

ModelTierHumanloopLangChainNoneOtherA rate
Gemini 2.5 FlashSmall143018232%
Devstral 2 2512Mid1804103100%
Qwen3 Coder NextMid01631120%
DeepSeek V3.2Mid47229536%
Llama 4 MaverickFrontier0901180%
Llama 4 ScoutSmall0641110%
Claude Haiku 4.5Small401120100%
DeepSeek R1 0528Frontier407121100%
MiMo V2 ProFrontier208122100%
Claude Opus 4.6Frontier000132n/a
Claude Sonnet 4.6Frontier000132n/a
Gemini 2.5 ProFrontier009123n/a
GLM 5 TurboFrontier0019113n/a
GPT 5.3 CodexFrontier000132n/a
GPT 5.4Frontier000132n/a
GPT 5.4 MiniMid003129n/a
Kimi K2.5Frontier003116n/a
MiniMax M2.7Frontier005124n/a
Mistral Small 4Mid001123n/a

Per-prompt breakdown

PromptTierHumanloopLangChainNoneOtherA rate
ai-revenue-ops-copilotIntermediate1522436341%
ai-revenue-ops-copilotBeginner11191037037%
ai-revenue-ops-copilotAdvanced89238147%
ai-support-agent-platformBeginner3126433220%
ai-support-agent-platformIntermediate62539675%
ai-support-agent-platformAdvanced34539843%