This benchmark is a six-part semantic scoring test that assesses any model's effectiveness at relevant calibration tasks. QCalEval measures a model's ability to interpret experimental results, classify outcomes, evaluate their significance, assess fit quality and key features, and generate actionable next-step recommendations.

Ising-Calibration-1 repeatedly outperforms state-of-the-art open and closed models of a range of parameters. As shown in Figure 1, Ising Calibration 1 scores 3.27% better on average than Gemini 3.1 Pro, 9.68% better than Claude Opus 4.6, and 14.5% better than GPT 5.4.