MMSearch-R1-7B
Introduction
MMSearch-R1-7B is a search-augmented LMM trained with end-to-end reinforcement learning, equipped with the ability to invoke multimodal search tools on demand. In 2025-08, we update this model by integrating improved reasoning capabilities. Please check our blog.
Model Details
Updated Model Performance
| Models |
MMK12 |
MathVerse (testmini) |
MathVision (testmini) |
MathVista (testmini) |
MMMU (val) |
AI2D |
ChartQA |
MME |
RealworldQA |
OCRBench |
DocVQA |
MMBench |
MMStar |
MiaBench |
| Qwen2.5-VL-7B |
34.4 |
46.2 |
24.0 |
66.6 |
49.8 |
93.3 |
94.4 |
630.4/1685.2 |
68.5 |
85.2 |
94.6 |
82.9 |
62.6 |
81.7 |
| General Search |
43.6 |
52.0 |
27.3 |
74.7 |
56.1 |
94.6 |
94.0 |
718.9/1775.3 |
65.5 |
77.8 |
89.4 |
84.0 |
60.4 |
44.4 |
| Models |
Infoseek |
MMSearch |
FVQA |
SimpleVQA |
| Qwen2.5-VL-7B |
20.1 |
12.8 |
20.3 |
38.4 |
| MMSearch |
55.1 |
53.8 |
58.4 |
57.4 |
| General Search |
52.0 |
54.9 |
52.8 |
57.0 |
Citation
@article{wu2025mmsearch,
title={MMSearch-R1: Incentivizing LMMs to Search},
author={Wu, Jinming and Deng, Zihao and Li, Wei and Liu, Yiding and You, Bo and Li, Bo and Ma, Zejun and Liu, Ziwei},
journal={arXiv preprint arXiv:2506.20670},
year={2025}
}