Fine-grained Multi-Image Understanding on VLM2-Bench benchmark leaderboard · SOTA2 Research

Fine-grained Multi-Image Understanding on VLM2-Bench

95.06Matching ScoreHuman-Level

Evaluation Results

Method	Links
Human-Level2026.04		95.06	98.11	94.23	96.02	91.29	92.87	97.08	91.17	94.48
MiCo-7B2026.04		57.14	67.12	56.67	81.94	58	57.5	65	62	63.17
MM-Eureka-7B2026.04		55.6	47.03	52.5	74.1	54	60	77.5	51	58.97
CGC-8B2026.04		48.85	56.14	70.28	84.72	76	77.5	83	94	73.81
VLAA-Thinker-7B2026.04		47.49	63.03	61.4	72.2	55	57.5	71	51	59.83
CGC-7B2026.04		42.11	50.22	61.39	72.36	58.5	64.17	82	79	63.72
NoisyRollout-7B2026.04		40.93	43.83	50.83	63.33	34.5	63.33	70.5	47	51.78
ThinkLite-VL-7B2026.04		40.45	46.58	62.5	75.56	49.5	62.5	77.5	51	58.2
Qwen2.5-VL-7B2026.04		35.91	43.38	41.72	71.39	47.5	59.76	80	69	56.08
InternVL2.5-26B2026.04		30.5	30.59	51.48	43.33	52.5	59.67	59.5	61.25	48.6
Qwen3-VL-8B2026.04		27.03	48.86	66.39	80	70.5	73.33	80	88	66.76
InternVL3-8B2026.04		23.94	29.68	64.17	61.67	39.5	55	63	55	49
InternVL2.5-8B2026.04		21.24	26.53	55.23	53.33	46.5	60	51.5	52	45.79
LLaVA-Video-7B2026.04		18.53	12.79	62.47	54.72	28.5	66.91	62	25	41.37
Qwen2-VL-7B2026.04		18.07	19.18	61.84	68.08	37.5	67.92	72	47	48.95
mPLUG-Owl2-7B2026.04		17.37	18.26	62.97	49.17	31	58.06	63	29	41.1
LLaVA-OV-7B2026.04		16.6	13.7	56.17	47.22	27.5	46.67	62	37	38.36
LongVQA-7B2026.04		14.29	12.98	49.47	46.53	29	41.56	58	25	34.6