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LLM Coding Agents
Methodology

Cursor vs LangChain

CursorCUCursorvsLALangChain
CursorLangChain
71%
29%

Leading: Cursor (70.8%)

Statistics

MetricValue
Cursor wins288
LangChain wins119
Abstains (no tool)254
Other tool chosen228
Decisive cases407
Cursor win rate (unweighted)70.8%
95% CI66.2% - 75.0%
Cursor win rate (weighted)70.8%

Comments

Cursor

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LangChain

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Per-model breakdown

ModelTierCursorLangChainNoneOtherA rate
GLM 5 TurboFrontier48000100%
Claude Opus 4.6Frontier27147066%
GPT 5.4 MiniMid3714697%
GPT 5.3 CodexFrontier31098100%
GPT 5.4Frontier31095100%
Claude Sonnet 4.6Frontier290190100%
DeepSeek V3.2Mid22618279%
MiniMax M2.7Frontier175101577%
MiMo V2 ProFrontier219101710%
Kimi K2.5Frontier200213100%
Qwen3 Coder NextMid1176236%
DeepSeek R1 0528Frontier01718130%
Gemini 2.5 FlashSmall0172290%
Mistral Small 4Mid130208100%
Llama 4 MaverickFrontier01220160%
Devstral 2 2512Mid46171840%
Gemini 2.5 ProFrontier50538100%
Llama 4 ScoutSmall0516260%
Claude Haiku 4.5Small102321100%

Per-prompt breakdown

PromptTierCursorLangChainNoneOtherA rate
ai-revenue-ops-copilotAdvanced692324775%
ai-revenue-ops-copilotIntermediate751315785%
ai-support-agent-platformAdvanced721506383%
ai-support-agent-platformIntermediate2230752442%
ai-revenue-ops-copilotBeginner3020802060%
ai-support-agent-platformBeginner2018961753%