Dev Tools · 2h ago
Measuring LLM output consistency: a practical method
A developer tested four LLMs (GPT-4o, Claude, Gemini, Perplexity) on 10 buyer-intent questions, finding low agreement across models. To distinguish genuine differences from non-determinism, they measured self-consistency by re-running each model three times. Self-consistency was much higher than cross-consistency, confirming models truly differ in their outputs.
Meridian48 take
The article offers a solid methodology for evaluating LLM reliability, but the small sample size (10 questions, one vertical) limits generalizability.
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How do you measure something that gives a different answer every time? →
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