SOURCE-LINKED INTELLIGENCE
API Benchmark Scores Do Not Reliably Transfer to Chatbot Interfaces
Benchmark scores are a central currency in model releases: they inform purchasing decisions, shape public trust, and influence policy. Yet, a key assumption underlying benchmark scores is that the model performance measured through APIs faithfully reflects the behavior of deployed systems. We challenge this assumption by auditing ChatGPT, Claude, and Gemini across seven systems and nine benchmarks spanning general capability, social bias, and sycophancy. We find systematic API--interface differences in both accuracy and consistency. On average, API evaluations score 3.4 percentage points highe
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T15:08:37.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.