Multimodal Retrieval and Understanding on MMEB V2 benchmark leaderboard · SOTA2 Research

Multimodal Retrieval and Understanding on MMEB V2

70Image CLS AccuracyLaME

Evaluation Results

Method	Links
LaME2026.06		70	71	73.1	85.8	73	51	64.8	40.3	44.6	50.8	81.5	58.2	85	68.2	75.9	68.8
Ops-MM-Embed2026.06		69.7	69.6	73.1	87.2	72.7	59.7	62.2	45.7	43.2	53.8	80.1	59.6	79.3	67.8	74.4	68.9
Ops-MM-Embed2026.06		68.1	65.1	69.2	80.9	69	53.6	55.7	41.8	33.7	47.6	76.4	53.2	77.6	32.6	65.5	63
LaME2026.06		67.6	66.2	70.5	81.2	69.3	45.6	52.3	36.3	43.5	44.5	78.2	48.4	82.8	55.4	72.1	64.4
UME-R12026.06		67.1	69.2	71.9	84.9	71.3	48.6	60.7	38.2	39.3	47.5	75.7	50.5	83.7	37.6	67.1	64.5
PLUME2026.06		66.5	59.2	67.6	79.7	66.3	45	52.3	33.5	46.7	44.1	72.1	49.8	78.1	57.4	67.5	61.6
UME-R12026.06		64.8	62.8	67.6	77.2	66.6	44.3	51	32.9	39.7	42.2	72.4	46.2	79.2	28.9	62.5	59.7
CAFe2026.06		63.6	61.7	69.1	87.6	67.6	35.8	58.7	34.4	39.5	42.4	70.7	49.6	79.5	38.1	63.9	60.6
VLM2Vec2026.06		62.7	56.9	69.4	82.2	65.5	39.1	30	29	40.6	34	56.9	9.4	59.1	38.1	46.4	52.3
VLM2Vec-V22026.06		62	56.3	69.5	77.3	64.9	39.3	34.3	28.8	38.5	34.9	75.5	44.9	79.4	39.4	65.4	58
LamRA2026.06		59.2	26.5	70	62.7	54.1	39.3	42.6	24.3	34.6	35.2	22	11.5	37.4	21	23.9	40.4
VLM2Vec2026.06		58.7	49.3	65	72.9	59.7	33.4	30.5	20.6	33	29	49.8	13.5	51.8	33.5	41.6	47
GME2026.06		57.7	34.7	71.2	59.3	56	37.4	50.4	28.4	38.2	38.6	89.4	55.6	85	44.4	75.2	57.8
GME2026.06		54.4	29.9	66.9	55.5	51.9	34.9	42	25.6	32.4	33.9	86.1	54	82.5	43.1	72.7	54.1
LamRA2026.06		51.7	34.1	66.9	56.7	52.4	32.9	42.6	23.2	37.6	33.7	56.3	33.3	58.2	40.1	50.2	47.4
ColPali-V1.32026.06		40.5	11.5	48.2	39.8	34.9	26.6	37.8	21.5	26.2	28.2	84.6	54.8	81	33.1	70.1	44.2