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Multimodal Reward Modeling on Multimodal RewardBench

88.79Accuracy

Gemini 3.1 Pro

Updated 1mo ago

Evaluation Results

Method
Gemini 3.1 Pro 2026.04	88.79	-
Gemini 3.0 Flash 2026.04	87.9	-
Gemini-2.5-Pro 2026.02	85.4	-
EGT 2026.02	84.3	-
Qwen3-VL-32B-Instruct 2026.04	83.02	-
Gemini-2.5-Flash 2026.02	82.5	-
Gemini 3.1 Flash-Lite 2026.04	82.25	-
Claude 4.6 Opus 2026.04	82.23	-
R1-Reward 2026.02	82.2	-
Qwen3-VL-30B-A3B-Instruct 2026.04	82.06	-
GPT-5.4 2026.04	81.91	-
Qwen3-VL-32B-Instruct 2026.04	81.19	-
DT2IT-MRM (Qwen3-VL) 2026.04	79.5	79.3
Qwen3-VL-32B-Instruct 2026.04	79.35	-
DT2IT-MRM (Qwen2.5-VL) 2026.04	77.7	77.7
Qwen3-VL-30B-A3B-Instruct 2026.04	75.82	-
Skywork-VL Reward 2026.04	74.25	-
Qwen3-VL-30B-A3B-Instruct 2026.04	72.49	-
Claude-3.7-Sonnet (2025-02-24) 2026.02	71.9	-
GPT-4o 2026.02	71.5	-
Omni-RewardModel-BT 2026.04	71.3	70.5
Qwen2-VL-72B 2026.02	70.9	-
GPT-4o (2024-08-06) 2026.02	70.8	-
IXC-2.5-Reward 2026.04	69.12	-
Skywork-VL Reward* 2026.04	67.9	74.4
MM-RLHF-Reward 2026.02	67.1	-
IXC-2.5-Reward 2026.02	66.6	-
PhyCritic-7B 2026.02	65.9	-
UnifiedReward* 2026.04	65.7	65.7
BaseReward (Qwen2.5-VL) 2026.04	65.7	72.8
UnifiedReward-Think* 2026.04	65.2	62.1
Eagle-2.5-8B 2026.02	64.4	-
Qwen2.5-VL-7B 2026.02	64	-
Gemini-1.5-Pro 2026.04	63.5	71.9
GPT-4o 2026.04	62.6	70.8
Claude-3.5-Sonnet 2026.04	62.6	71.5
MM-RLHF-Reward 2026.04	61.7	67.1
GPT-5.2* 2026.04	60.7	75.3
IXC-2.5-Reward 2026.04	60.7	66.6
LLaVA-Critic* 2026.04	60.7	48.9
Llama-3.2-Vision-Instruct 2026.04	60	61.2
InternVL3-8B 2026.04	59.6	63.6
Claude-3.7-Sonnet 2026.04	58.4	71.9
Llama-3.2-Vision-Instruct 2026.04	57.8	51.2
Qwen2-VL-72B-Instruct 2026.04	56.4	70.9
Cosmos-R1-7B 2026.02	54.8	-
VITA-1.5 2026.02	53.6	-
Robobrain2.0-7B 2026.02	50.5	-
R1-Reward* 2026.04	47	53
SliME 2026.02	42	-