From Pixels to Words -- Towards Native Vision-Language Primitives at Scale

Benchmark Model Rank Results
object-hallucination-evaluation-on-popeNEO-9B#6F1: 88.4
infographic-visual-question-answering-on-infovqaNEO-2.2B#7ANLS: 63.2
visual-question-answering-vqa-on-hallusionbench-average-accuracyNEO-9B#20Accuracy: 46.4
visual-question-answering-on-docvqa-testNEO-2.2B#45ANLS: 0.899
optical-character-recognition-ocr-on-ocrbenchNEO-9B#57Score: 777
visual-question-answering-on-mm-vetNEO (Qwen3-8B)#57GPT-4 score: 53.6
visual-question-answering-on-mm-vetNEO (Qwen3-1.7B)#69GPT-4 score: 49.6
chart-question-answering-on-chartqaNEO-9B#591:1 Accuracy: 82.1
vision-language-understanding-on-mmstarNEO-9B#76Accuracy: 62.4
multimodal-reasoning-on-mmmuNEO-9B#77Accuracy: 54.6