DeepTumorVQA - Recognition: leaderboard
Metric: Accuracy (%) on the Recognition-stage questions (binary: lesion presence, organ enlargement; chance 50%) of the balanced 10,000-question multiple-choice test subset of DeepTumorVQA (42 subtypes over abdominal 3D CT volumes), direct inference zero-shot with each model's native input (2D organ-centred slices for 2D models, the full 3D volume for 3D models); higher is better. Source: arxiv.org. Saturation forecast: Around 2031. 14 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Qwen 3.5 9B | 58.4 |
| 2 | Qwen 3.5 35B A3B | 53 |
| 3 | InternVL3-8B | 52.5 |
| 4 | MedGemma 1.5 4B | 48.3 |
| 5 | Gemini 3 Flash | 42.6 |
Interactive version: theaggregate.ai/benchmark?slug=deeptumorvqa-recognition · How It Works · Data refreshed daily, snapshot 2026-10-07.