Inference backends change the model behavior teams observe
A fully crossed study of three models, five inference frameworks, six benchmarks, and four generation modes found significant score changes even under greedy decoding; backend choice explained roughly 39% of ordinary out-of-box variability.
Why it matters: A benchmark result is partly a property of the serving stack and defaults, not only the model weights and prompt.