SOURCE-LINKED INTELLIGENCE
Text, Pixels, or Both? Evaluating Input Representations for Multimodal Document QA
Every document QA system begins with a choice that is rarely studied on its own: whether to feed the model page images, extracted text, or both. We isolate this choice, holding the prompt, judge, and scoring pipeline fixed, across four commercial model endpoints, two corpora, and two context regimes (gold evidence pages and the full document). On documents that fit the image budget, page images lead on accuracy at every document length on both corpora, but this advantage carries a growing latency and cost premium: text latency stays roughly flat as documents lengthen while image latency rises
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T22:26:49.000Z
First collected: 2026-09-23T12:01:45.602Z. This is not the publication date.