lmms-lab/MMSearch-R1-7B-0807

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

• Model name: MMSearch-R1-7B-0807
• Architecture: Qwen2.5-VL-7B base model, fine-tuned with Reinforcement Learning (GRPO)
• Model type: Multimodal Large Language Model with Search-Augmentation
• Languages: English(primary), multilingual(partially)
• License: Apache license 2.0
• Paper: MMSearch-R1: Incentivizing LMMs to Search
• Code: EvolvingLMMs-Lab/multimodal-search-r1

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}
}