Long context claims vs. real recall past 100k tokens

Been testing several models on needle-in-haystack tasks using messy real documents instead of clean synthetic text. The advertised 200k to 1M windows handle single-fact retrieval fine, but degrade fast when an answer requires joining three or four scattered passages. Effective context feels