DALPHIN (Contextual) - Multiple Choice: leaderboard
Case-specific multiple-choice questions with three to six options, written by the contributing pathologists for the 300 cases of the DALPHIN pathology copilot benchmark (Lems et al., 2026), on morphology, ancillary testing, diagnosis, clinical knowledge and mixed reasoning. Accuracy on a 0-1 scale; higher is better. Contextual scenario: each case's questions are asked in sequence within one conversation, so earlier answers stay in context.
Metric: Accuracy (0-1; one case-specific multiple-choice question per case with three to six options, written by the contributing pathologist; 300 questions; an unanswered question counts as wrong; contextual scenario: all questions of a case asked in sequence in one conversation). Source: arxiv.org. Saturation forecast: Around February 2027. 3 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Gemini 2.5 Pro (Medium) | 0.76 | #262 (Gemini 2.5 Pro) |
| 2 | GPT-5 (Medium) | 0.74 | #163 (GPT-5) |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=dalphin-contextual-multiple-choice · How It Works · Data refreshed daily, snapshot 2026-11-12.