Spaces:
Running
Running
score update
#106
by
MINGYISU
- opened
- app.py +35 -5
- archive/page_old_scores.jsonl +19 -0
- datasets.py +1 -1
- rankings/image_ranking.csv +80 -62
- rankings/image_ranking.jsonl +0 -0
- rankings/mmeb_ranking.csv +43 -25
- rankings/mmeb_ranking.jsonl +42 -24
- rankings/video_ranking.csv +43 -25
- rankings/video_ranking.jsonl +42 -24
- rankings/visdoc_ranking.csv +43 -25
- rankings/visdoc_ranking.jsonl +42 -24
- scores/LamRA-Ret-Qwen2.5VL-7b.json +0 -0
- scores/LamRA-Ret.json +0 -0
- scores/VLM2Vec-V1-Qwen2VL-2B.json +0 -0
- scores/VLM2Vec-V1-Qwen2VL-7B.json +0 -0
- scores/VLM2Vec-V2.0-Qwen2VL-2B.json +0 -0
- scores/colpali-v1.3.json +0 -0
- scores/gme-Qwen2-VL-2B-Instruct.json +0 -0
- scores/gme-Qwen2-VL-7B-Instruct.json +0 -0
- utils.py +9 -10
- utils_v2.py +28 -12
app.py
CHANGED
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@@ -41,6 +41,7 @@ with gr.Blocks() as block:
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)
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df = get_df()
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df2 = v2.get_df()
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min_size2, max_size2 = get_size_range(df2)
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@@ -73,7 +74,10 @@ with gr.Blocks() as block:
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refresh_button2 = gr.Button("Refresh")
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# save a summary of rankings
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v2.save_ranking_summary(
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def update_with_tasks_v2(*args):
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return update_table_v2(*args)
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@@ -122,6 +126,8 @@ with gr.Blocks() as block:
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max_height=2400,
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)
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v2.save_ranking_summary(df2_i, 'image_ranking')
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# table 3, video scores only
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with gr.TabItem("💽 Video", elem_id="tab-video", id=3):
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@@ -137,26 +143,50 @@ with gr.Blocks() as block:
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max_height=2400,
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)
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v2.save_ranking_summary(df2_v, 'video_ranking')
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# table 4, visual document scores only
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with gr.TabItem("📑 Visual Doc", elem_id="tab-visdoc", id=4):
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gr.Markdown(v2.TABLE_INTRODUCTION_D)
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df2_d = v2.rank_models(df2[v2.COLUMN_NAMES_D], 'Visdoc-Overall')
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data_component5 = gr.components.Dataframe(
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value=df2_d,
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headers=
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type="pandas",
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datatype=
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interactive=False,
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visible=True,
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max_height=2400,
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)
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v2.save_ranking_summary(df2_d, 'visdoc_ranking')
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# table 5
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with gr.TabItem("📝 About", elem_id="tab-about", id=5):
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gr.Markdown(LEADERBOARD_INFO, elem_classes="markdown-text")
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# gr.Image("overview.png", width=900, label="Dataset Overview")
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# table 6
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with gr.TabItem("🚀 Submit here! ", elem_id="tab-submit", id=6):
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)
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df = get_df()
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+
df['Date'] = 'unknown' # placeholder before fixing date format in v2
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df2 = v2.get_df()
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min_size2, max_size2 = get_size_range(df2)
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refresh_button2 = gr.Button("Refresh")
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# save a summary of rankings
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v2.save_ranking_summary(df2_all, 'mmeb_ranking')
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download_overall_but = gr.DownloadButton("Download MMEB Ranking (CSV)", value=v2.download_ranking(df2[v2.COLUMN_NAMES], 'mmeb_ranking'))
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download_overall_but_json = gr.DownloadButton("Download MMEB Ranking (JSON)", value=v2.download_ranking(df2[v2.COLUMN_NAMES], 'mmeb_ranking', format='json'))
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+
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def update_with_tasks_v2(*args):
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return update_table_v2(*args)
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max_height=2400,
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)
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v2.save_ranking_summary(df2_i, 'image_ranking')
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download_i_but = gr.DownloadButton("Download Image Ranking (CSV)", value=v2.download_ranking(df2_i, 'image_ranking'))
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download_i_but_json = gr.DownloadButton("Download Image Ranking (JSON)", value=v2.download_ranking(df2_i, 'image_ranking', format='json'))
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# table 3, video scores only
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with gr.TabItem("💽 Video", elem_id="tab-video", id=3):
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max_height=2400,
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)
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v2.save_ranking_summary(df2_v, 'video_ranking')
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download_v_but = gr.DownloadButton("Download Video Ranking (CSV)", value=v2.download_ranking(df2_v, 'video_ranking'))
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download_v_but_json = gr.DownloadButton("Download Video Ranking (JSON)", value=v2.download_ranking(df2_v, 'video_ranking', format='json'))
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# table 4, visual document scores only
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with gr.TabItem("📑 Visual Doc", elem_id="tab-visdoc", id=4):
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gr.Markdown(v2.TABLE_INTRODUCTION_D)
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df2_d = v2.rank_models(df2[v2.COLUMN_NAMES_D+['ViDoSeek-page', 'MMLongBench-page']], 'Visdoc-Overall')
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# ================= HARD CODED TEMPORARY FIX =================
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temp_df_vd = pd.read_json('archive/page_old_scores.jsonl', orient='records', lines=True)
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df2_d = df2_d.merge(temp_df_vd, on='Models', how='left')
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def special_process_visdoc(row):
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if not pd.isna(row['ViDoSeek-page-old']):
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row['ViDoSeek-page'] = '⚠️! Please fix this score!'
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if not pd.isna(row['MMLongBench-page-old']):
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row['MMLongBench-page'] = '⚠️! Please fix this score!'
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return row
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df2_d = df2_d.apply(special_process_visdoc, axis=1)
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df2_d = df2_d.rename(columns={
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'ViDoSeek-page': 'ViDoSeek-page-fixed',
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'MMLongBench-page': 'MMLongBench-page-fixed'
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})
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temp_col_names_d = v2.COLUMN_NAMES_D + ['ViDoSeek-page-fixed', 'MMLongBench-page-fixed', 'ViDoSeek-page-old', 'MMLongBench-page-old']
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print(temp_col_names_d)
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temp_data_type_d = v2.DATA_TITLE_TYPE_D + ['number', 'number']
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df2_d[['ViDoSeek-page-old', 'MMLongBench-page-old']] = df2_d[['ViDoSeek-page-old', 'MMLongBench-page-old']].fillna('✅')
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df2_d = df2_d[temp_col_names_d]
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# ==========================================================
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data_component5 = gr.components.Dataframe(
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value=df2_d,
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headers=temp_col_names_d,
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type="pandas",
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datatype=temp_data_type_d,
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interactive=False,
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visible=True,
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max_height=2400,
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)
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v2.save_ranking_summary(df2_d, 'visdoc_ranking')
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download_vd_but = gr.DownloadButton("Download Visual Document Ranking (CSV)", value=v2.download_ranking(df2_d, 'visdoc_ranking'))
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download_vd_but_json = gr.DownloadButton("Download Visual Document Ranking (JSON)", value=v2.download_ranking(df2_d, 'visdoc_ranking', format='json'))
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# table 5
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with gr.TabItem("📝 About", elem_id="tab-about", id=5):
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gr.Image("overview.png", width=900, label="Dataset Overview")
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gr.Markdown(LEADERBOARD_INFO, elem_classes="markdown-text")
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# table 6
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with gr.TabItem("🚀 Submit here! ", elem_id="tab-submit", id=6):
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archive/page_old_scores.jsonl
ADDED
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{"Models":"<a href=\"https:\/\/interestfm-tte.github.io\/\">IFM-TTE-7B<\/a>","ViDoSeek-page-old":50.29,"MMLongBench-page-old":28.18}
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{"Models":"<a href=\"https:\/\/console.volcengine.com\/ark\/region:ark+cn-beijing\/model\/detail?Id=doubao-embedding-vision\">seed1.6-embedding-1215<\/a>","ViDoSeek-page-old":22.29,"MMLongBench-page-old":17.15}
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{"Models":"WeMM-Embedding-8B","ViDoSeek-page-old":23.34,"MMLongBench-page-old":17.05}
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{"Models":"<a href=\"https:\/\/github.com\/360CVGroup\/RzenEmbed\">RzenEmbed-v2-7B<\/a>","ViDoSeek-page-old":23.09,"MMLongBench-page-old":15.62}
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{"Models":"RzenEmbed-v1-7B","ViDoSeek-page-old":23.06,"MMLongBench-page-old":16.1}
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{"Models":"Taichu-UniRetriever-v1-2B","ViDoSeek-page-old":20.92,"MMLongBench-page-old":16.49}
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{"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-7B\">e5-omni-7B<\/a>","ViDoSeek-page-old":23.11,"MMLongBench-page-old":15.78}
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{"Models":"WeMM-Embedding-2B","ViDoSeek-page-old":22.27,"MMLongBench-page-old":16.53}
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{"Models":"RzenEmbed-v1-2B","ViDoSeek-page-old":22.89,"MMLongBench-page-old":16.21}
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{"Models":"<a href=\"https:\/\/seed1-6-embedding.github.io\">seed-1.6-embedding<\/a>","ViDoSeek-page-old":22.8,"MMLongBench-page-old":15.57}
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{"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-3B\">e5-omni-3B<\/a>","ViDoSeek-page-old":22.38,"MMLongBench-page-old":15.0}
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{"Models":"Crotchet-embedding-2B","ViDoSeek-page-old":78.36,"MMLongBench-page-old":51.39}
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{"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-7B\">Ops-MM-embedding-v1-7B<\/a>","ViDoSeek-page-old":22.47,"MMLongBench-page-old":15.89}
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{"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-7B\">UME-R1-7B<\/a>","ViDoSeek-page-old":21.28,"MMLongBench-page-old":12.32}
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{"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-2B\">Ops-MM-embedding-v1-2B<\/a>","ViDoSeek-page-old":21.44,"MMLongBench-page-old":13.06}
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{"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-7B<\/a>","ViDoSeek-page-old":22.52,"MMLongBench-page-old":13.32}
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{"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-2B\">UME-R1-2B<\/a>","ViDoSeek-page-old":21.2,"MMLongBench-page-old":11.9}
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{"Models":"<a href=\"https:\/\/github.com\/GaryGuTC\/UniME-v2\">UniME-V2-LLaVA-OneVision-7B<\/a>","ViDoSeek-page-old":22.89,"MMLongBench-page-old":11.96}
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{"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-0.5B<\/a>","ViDoSeek-page-old":17.62,"MMLongBench-page-old":9.95}
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datasets.py
CHANGED
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@@ -18,7 +18,7 @@ DATASETS = {
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"ViDoRe-V1": ['ViDoRe_arxivqa', 'ViDoRe_docvqa', 'ViDoRe_infovqa', 'ViDoRe_tabfquad', 'ViDoRe_tatdqa', 'ViDoRe_shiftproject', 'ViDoRe_syntheticDocQA_artificial_intelligence', 'ViDoRe_syntheticDocQA_energy', 'ViDoRe_syntheticDocQA_government_reports', 'ViDoRe_syntheticDocQA_healthcare_industry'],
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"ViDoRe-V2": ["ViDoRe_esg_reports_human_labeled_v2","ViDoRe_biomedical_lectures_v2_multilingual", "ViDoRe_economics_reports_v2_multilingual", "ViDoRe_esg_reports_v2_multilingual"], # "ViDoRe_biomedical_lectures_v2", "ViDoRe_economics_reports_v2", "ViDoRe_esg_reports_v2"
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"VisRAG": ['VisRAG_ArxivQA', 'VisRAG_ChartQA', 'VisRAG_MP-DocVQA', 'VisRAG_SlideVQA', 'VisRAG_InfoVQA', 'VisRAG_PlotQA'],
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"VisDoc-OOD": ['ViDoSeek-
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},
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"video": {
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"V-CLS": ['K700', 'UCF101', 'HMDB51', 'SmthSmthV2', 'Breakfast'],
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"ViDoRe-V1": ['ViDoRe_arxivqa', 'ViDoRe_docvqa', 'ViDoRe_infovqa', 'ViDoRe_tabfquad', 'ViDoRe_tatdqa', 'ViDoRe_shiftproject', 'ViDoRe_syntheticDocQA_artificial_intelligence', 'ViDoRe_syntheticDocQA_energy', 'ViDoRe_syntheticDocQA_government_reports', 'ViDoRe_syntheticDocQA_healthcare_industry'],
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"ViDoRe-V2": ["ViDoRe_esg_reports_human_labeled_v2","ViDoRe_biomedical_lectures_v2_multilingual", "ViDoRe_economics_reports_v2_multilingual", "ViDoRe_esg_reports_v2_multilingual"], # "ViDoRe_biomedical_lectures_v2", "ViDoRe_economics_reports_v2", "ViDoRe_esg_reports_v2"
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"VisRAG": ['VisRAG_ArxivQA', 'VisRAG_ChartQA', 'VisRAG_MP-DocVQA', 'VisRAG_SlideVQA', 'VisRAG_InfoVQA', 'VisRAG_PlotQA'],
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"VisDoc-OOD": ['ViDoSeek-doc', 'MMLongBench-doc'] # 'ViDoSeek-page', 'MMLongBench-page'
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},
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"video": {
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"V-CLS": ['K700', 'UCF101', 'HMDB51', 'SmthSmthV2', 'Breakfast'],
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rankings/image_ranking.csv
CHANGED
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-
Rank,Models,Model Size(B),Image-Overall,I-CLS,I-QA,I-RET,I-VG,VOC2007,N24News,SUN397,ObjectNet,Country211,Place365,ImageNet-1K,HatefulMemes,ImageNet-A,ImageNet-R,OK-VQA,A-OKVQA,DocVQA,InfographicsVQA,ChartQA,Visual7W,ScienceQA,GQA,TextVQA,VizWiz,VisDial,CIRR,VisualNews_t2i,VisualNews_i2t,MSCOCO_t2i,MSCOCO_i2t,NIGHTS,WebQA,FashionIQ,Wiki-SS-NQ,OVEN,EDIS,MSCOCO,RefCOCO,RefCOCO-Matching,Visual7W-Pointing
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1,"<a href=""https://
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38,"<a href=""https://
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40,"<a href=""https://huggingface.co/
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41,"<a href=""https://huggingface.co/
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42,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-
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43,"<a href=""https://huggingface.co/
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44,"<a href=""https://
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| 1 |
+
Rank,Models,Model Size(B),Date,Image-Overall,I-CLS,I-QA,I-RET,I-VG,VOC2007,N24News,SUN397,ObjectNet,Country211,Place365,ImageNet-1K,HatefulMemes,ImageNet-A,ImageNet-R,OK-VQA,A-OKVQA,DocVQA,InfographicsVQA,ChartQA,Visual7W,ScienceQA,GQA,TextVQA,VizWiz,VisDial,CIRR,VisualNews_t2i,VisualNews_i2t,MSCOCO_t2i,MSCOCO_i2t,NIGHTS,WebQA,FashionIQ,Wiki-SS-NQ,OVEN,EDIS,MSCOCO,RefCOCO,RefCOCO-Matching,Visual7W-Pointing
|
| 2 |
+
1,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B"">Qwen3-VL-Embedding-8B</a>",8.14,2026-01-06,80.12,74.19,81.14,80.16,92.3,93.4,80.6,82.7,79.9,27.3,47.6,81.9,77.5,77.1,93.9,77.8,72.9,96.3,88.4,74.3,70.9,81.0,92.6,92.8,64.4,87.6,74.9,81.1,85.7,81.1,79.1,72.7,91.8,44.5,87.9,79.2,96.3,86.3,95.7,91.1,96.1
|
| 3 |
+
2,QQMM-embed-v3,8.29,2025-12-30,78.21,74.79,75.11,78.86,92.58,93.6,82.7,84.8,76.3,33.7,52.1,84.0,80.3,68.0,92.4,74.4,70.6,95.5,75.0,68.8,65.3,78.9,78.9,87.2,56.5,87.2,71.0,81.1,84.6,82.9,79.4,69.4,92.7,45.6,82.6,74.7,95.1,86.7,95.6,92.7,95.3
|
| 4 |
+
3,WeMM-Embedding-8B,8.77,2025-12-16,78.09,73.55,76.1,78.62,92.88,94.5,81.7,82.9,87.8,32.2,48.0,82.8,70.0,63.6,92.0,73.4,64.5,95.6,85.2,72.1,63.6,81.5,78.6,88.9,57.6,88.9,70.7,81.7,84.9,81.2,78.2,69.0,91.0,43.8,84.7,74.4,94.9,84.4,95.6,92.5,99.0
|
| 5 |
+
4,"<a href=""https://console.volcengine.com/ark/region:ark+cn-beijing/model/detail?Id=doubao-embedding-vision"">seed1.6-embedding-1215</a>",unknown,2025-12-18,77.99,75.05,74.89,79.33,89.05,89.3,82.2,78.6,83.2,46.9,52.4,83.7,70.3,70.9,93.0,74.9,65.8,95.1,86.2,73.1,58.0,78.7,76.3,85.6,55.2,86.2,69.9,83.8,83.7,81.3,77.8,70.7,92.7,50.4,84.6,74.1,96.7,77.3,93.5,93.8,91.6
|
| 6 |
+
5,"<a href=""https://interestfm-tte.github.io/"">IFM-TTE-7B</a>",8.29,2025-10-11,77.9,76.74,78.49,74.58,89.3,83.4,82.1,78.8,74.0,60.5,65.5,84.0,75.1,73.6,90.4,83.4,77.3,95.5,82.3,83.2,73.8,67.3,79.1,87.9,55.1,84.6,66.4,79.2,82.5,77.7,72.6,69.4,91.1,32.4,73.6,69.9,95.5,85.4,91.7,91.9,88.2
|
| 7 |
+
6,"<a href=""https://seed1-6-embedding.github.io"">seed-1.6-embedding</a>",unknown,2025-06-17,77.78,76.06,73.97,77.9,91.25,91.9,82.9,80.8,85.4,47.7,52.8,84.2,73.7,73.1,88.1,74.2,64.6,96.2,82.9,69.2,59.6,79.2,74.7,85.1,54.0,84.6,65.0,83.4,84.5,78.8,77.4,72.1,91.7,49.0,79.6,77.2,91.5,82.1,95.5,93.0,94.4
|
| 8 |
+
7,WeMM-Embedding-2B,2.13,2025-12-16,76.08,72.12,72.6,76.55,93.28,93.7,78.7,83.0,88.5,28.9,46.6,83.6,66.0,60.6,91.6,66.4,57.4,95.1,79.7,66.3,66.2,78.0,75.6,86.5,54.8,85.1,66.9,76.9,80.3,77.6,77.0,69.6,91.3,43.2,83.9,73.5,93.3,86.1,96.5,92.1,98.4
|
| 9 |
+
8,"<a href=""https://github.com/360CVGroup/RzenEmbed"">RzenEmbed-v2-7B</a>",8.29,2025-09-20,75.92,70.61,71.67,78.5,92.1,91.4,84.0,82.7,72.0,29.7,48.1,84.1,62.4,61.5,90.2,73.1,63.1,94.6,76.8,69.2,63.2,60.7,74.6,86.3,55.1,85.6,67.2,82.6,85.8,81.1,78.0,69.0,92.4,41.5,79.8,81.8,97.2,83.5,94.9,93.2,96.8
|
| 10 |
+
9,"<a href=""https://github.com/QQ-MM/QQMM-embed"">QQMM-embed-v2</a>",8.29,2025-09-15,75.28,72.97,71.85,76.01,87.42,92.8,82.4,83.7,74.2,30.8,48.8,83.5,79.6,62.7,91.2,73.8,71.1,96.0,74.0,68.1,65.3,62.7,62.4,88.2,56.9,85.5,69.5,80.5,83.9,82.6,80.1,67.0,92.7,32.2,74.2,72.5,91.4,81.5,93.5,92.9,81.8
|
| 11 |
+
10,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B"">Qwen3-VL-Embedding-2B</a>",2.13,2026-01-06,74.96,70.34,74.27,74.85,88.55,92.7,71.2,81.7,79.4,24.4,45.1,78.1,65.8,71.6,93.4,66.2,61.1,95.0,76.5,65.5,64.4,73.6,88.1,90.4,61.9,81.5,64.9,73.4,75.9,77.3,74.6,69.5,89.9,38.8,83.5,76.4,92.5,81.7,96.1,82.5,93.9
|
| 12 |
+
11,UniVec-CoT-7B,8.29,unknown,74.11,70.04,73.45,72.05,92.1,89.9,82.1,81.4,64.5,27.6,44.9,83.0,75.2,62.6,89.2,73.4,64.7,95.8,85.3,85.0,57.9,62.4,71.0,85.4,53.6,85.6,56.9,78.8,81.1,77.8,75.9,66.8,90.9,21.7,72.2,70.5,86.4,86.1,93.3,93.5,95.5
|
| 13 |
+
12,OEmbedding-v1-7B,8.29,2025-10-14,74.05,70.56,70.02,74.67,90.97,89.2,82.0,79.0,72.6,31.2,46.0,84.5,70.5,59.9,90.7,73.2,63.3,95.2,74.4,69.4,60.5,54.8,68.9,86.2,54.3,85.8,65.9,82.5,86.0,81.7,76.8,68.2,90.8,25.6,69.9,73.5,89.4,81.8,95.6,94.1,92.4
|
| 14 |
+
13,ReCo-7B,8.29,2025-08-15,73.87,70.95,71.52,73.66,87.7,88.8,83.8,81.2,74.1,28.0,47.4,84.2,73.6,58.3,90.1,74.1,61.8,95.1,76.3,66.7,67.2,54.5,76.8,87.3,55.4,85.3,60.7,81.4,84.3,79.5,74.0,68.7,90.7,20.6,72.1,74.0,92.6,74.1,93.5,94.1,89.1
|
| 15 |
+
14,UniVec-7B,8.29,unknown,73.79,68.79,71.69,73.76,91.67,90.0,81.9,80.4,58.6,28.5,45.9,83.3,75.7,57.6,86.0,73.6,64.3,95.1,80.9,73.1,58.2,56.9,74.2,86.3,54.3,85.7,56.9,79.0,82.7,78.9,76.4,68.2,89.3,28.3,70.0,79.0,90.7,87.5,94.5,93.7,91.0
|
| 16 |
+
15,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-7B</a>",8.29,2025-11-24,73.7,65.78,73.58,74.12,92.5,89.5,81.0,78.7,59.4,25.4,45.4,78.7,67.8,48.4,83.5,72.6,63.6,95.8,82.9,75.5,66.9,59.5,77.9,87.6,53.5,85.8,59.8,79.2,83.1,81.2,76.0,69.5,90.1,29.6,69.5,73.2,92.5,84.2,95.8,94.0,96.0
|
| 17 |
+
16,RzenEmbed-v1-7B,8.29,2025-07-30,73.6,69.78,68.72,76.83,85.67,91.6,81.7,82.4,68.5,29.0,43.5,82.8,70.0,59.0,89.3,69.6,61.3,94.8,73.6,64.0,60.5,58.2,65.5,86.2,53.5,83.1,66.3,82.6,85.8,78.6,76.0,68.6,91.3,38.7,74.8,79.6,96.5,78.3,88.3,85.1,91.0
|
| 18 |
+
17,dp-embedding-v3-lite,8.29,2025-12-15,73.38,69.46,70.03,75.27,85.83,81.2,81.6,83.6,70.9,34.2,47.2,82.2,63.7,60.8,89.2,70.7,64.1,94.1,76.8,66.6,58.9,56.0,76.3,84.0,52.8,82.7,60.3,77.1,84.0,78.5,74.5,68.3,91.2,37.5,79.2,78.6,91.4,69.5,88.9,91.7,93.2
|
| 19 |
+
18,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-7B"">Ops-MM-embedding-v1-7B</a>",8.29,2025-07-02,72.72,69.65,69.58,73.09,87.15,84.8,82.1,81.0,69.7,28.5,45.6,81.1,75.7,57.8,90.2,70.6,60.0,94.7,73.6,65.2,58.4,49.9,79.9,86.9,56.6,81.8,55.2,80.1,84.3,79.3,72.1,66.2,91.9,24.3,74.3,73.2,94.4,73.9,90.4,92.7,91.6
|
| 20 |
+
19,TCE-v1,8.0,2025-10-31,72.36,67.89,70.28,72.31,88.85,91.6,81.7,78.8,53.8,20.2,46.4,81.3,75.4,59.6,90.1,71.5,61.4,95.0,81.0,72.0,57.8,58.7,69.4,83.6,52.4,86.7,57.8,77.9,81.8,79.0,77.3,68.1,89.3,25.6,66.2,65.4,92.6,85.2,93.7,91.4,85.1
|
| 21 |
+
20,"<a href=""https://github.com/QQ-MM/QQMM-embed"">QQMM-embed</a>",8.297,unknown,72.175,70.07,69.52,71.175,87.075,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 22 |
+
21,"<a href=""https://huggingface.co/raghavlite/B3_Qwen2_7B"">B3_Qwen2_7B</a>",8.29,unknown,72.0,70.0,66.5,74.1,84.6,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 23 |
+
22,"<a href=""https://github.com/GaryGuTC/UniME-v2"">UniME-V2-LLaVA-OneVision-7B</a>",8.03,2025-10-15,71.77,65.64,68.66,73.1,90.85,92.5,66.0,78.8,73.2,19.0,43.8,78.9,66.1,49.0,89.1,71.7,71.5,92.4,67.1,59.2,62.7,55.2,69.0,84.4,53.4,84.8,67.0,77.3,80.1,80.0,74.6,68.3,90.2,27.0,70.9,68.5,88.5,81.3,95.3,92.8,94.0
|
| 24 |
+
23,"<a href=""https://huggingface.co/zhibinlan/UME-R1-7B"">UME-R1-7B</a>",8.29,2025-10-20,71.25,67.09,69.18,71.9,84.85,90.8,82.3,80.3,42.3,25.0,46.8,80.4,79.0,53.9,90.1,71.7,58.7,93.8,79.2,75.1,55.2,53.7,69.3,83.5,51.6,80.7,55.3,76.8,82.0,78.3,71.4,68.1,90.9,23.4,72.5,71.4,92.0,72.7,91.4,91.1,84.2
|
| 25 |
+
24,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-7B"">e5-omni-7B</a>",8.0,2026-01-09,71.23,66.73,68.54,73.0,83.92,83.9,77.2,76.1,57.7,34.7,44.3,79.4,72.3,57.2,84.5,70.5,59.7,93.3,62.9,62.8,65.2,56.4,72.1,86.2,56.3,82.4,54.9,75.3,79.8,76.6,76.9,68.6,89.3,24.5,79.4,78.7,89.6,74.8,89.4,87.2,84.3
|
| 26 |
+
25,"<a href=""https://huggingface.co/DeepGlint-AI/UniME-LLaVA-OneVision-7B"">UniME(LLaVA-OneVision-7B-LoRA-Res336)</a>",8.03,unknown,70.7,66.8,66.6,70.5,90.9,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 27 |
+
26,"<a href=""https://huggingface.co/friedrichor/Unite-Instruct-Qwen2-VL-7B"">UNITE-Instruct-7B</a>",8.29,unknown,70.3,68.3,65.1,71.6,84.8,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 28 |
+
27,"<a href=""https://huggingface.co/zhibinlan/LLaVE-7B"">LLaVE-7B</a>",8.03,unknown,70.3,65.7,65.4,70.9,91.9,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 29 |
+
28,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-3B</a>",3.75,2025-11-24,70.2,62.4,69.55,69.97,92.0,89.7,81.0,74.6,55.4,21.0,44.4,76.5,60.3,38.3,82.8,71.4,60.4,94.7,76.4,68.3,62.4,53.0,71.9,83.6,53.4,83.6,57.0,75.1,80.8,76.5,74.4,66.0,89.9,18.9,66.3,68.2,82.9,83.8,95.3,93.9,95.0
|
| 30 |
+
29,"<a href=""https://huggingface.co/intfloat/mmE5-mllama-11b-instruct"">mmE5-mllama-11b-instruct</a>",10.6,unknown,69.8,67.6,62.6,71.0,89.6,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 31 |
+
30,"<a href=""https://arxiv.org/pdf/2503.19900"">interestFM-UIR-CAFe-7B</a>",8.03,unknown,69.8,65.2,65.6,70.0,91.2,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 32 |
+
31,"<a href=""https://huggingface.co/BAAI/BGE-VL-v1.5-mmeb"">BGE-VL-v1.5 (FT; LlaVA-1.6-Mistral)</a>",7.57,unknown,69.4,63.7,64.9,72.2,86.6,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 33 |
+
32,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-2B</a>",2.21,2025-11-24,69.21,65.82,65.94,70.05,83.3,86.9,80.5,74.6,65.5,25.3,42.4,76.4,65.8,49.5,91.3,66.9,56.1,93.4,68.2,56.9,61.1,47.1,73.8,83.0,52.9,82.9,56.9,75.3,81.3,75.3,73.4,67.5,89.7,19.5,63.9,68.6,86.3,67.4,90.5,91.3,84.0
|
| 34 |
+
33,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-2B"">Ops-MM-embedding-v1-2B</a>",2.21,2025-07-02,69.03,68.07,65.11,69.17,80.85,81.3,78.4,80.7,68.4,28.6,43.9,81.1,74.0,53.1,91.2,64.1,54.0,93.0,65.3,56.1,58.5,47.3,74.4,83.1,55.3,79.4,47.3,76.2,79.1,74.1,69.7,66.1,91.1,18.5,68.8,69.1,90.6,66.8,84.1,87.9,84.6
|
| 35 |
+
34,RzenEmbed-v1-2B,2.21,2025-07-16,68.53,65.29,61.7,73.81,77.85,89.6,74.0,78.4,71.3,24.5,41.3,80.9,58.6,49.5,84.8,60.0,53.2,90.5,59.3,51.8,57.1,47.5,60.4,83.8,53.4,79.1,62.7,78.0,81.4,76.7,73.6,67.9,91.0,33.8,74.9,74.6,92.0,68.5,86.0,74.8,82.1
|
| 36 |
+
35,Crotchet-embedding-2B,2.13,2025-12-31,68.18,62.56,65.93,68.24,87.67,78.7,46.6,75.0,73.8,20.0,42.6,77.7,66.0,57.2,88.0,59.7,54.6,92.0,74.7,80.4,50.0,52.9,59.8,82.8,52.4,80.5,57.8,70.1,69.7,77.3,74.0,65.3,88.9,26.4,67.2,58.2,83.5,89.8,90.8,87.1,83.0
|
| 37 |
+
36,"<a href=""https://huggingface.co/raghavlite/B3_Qwen2_2B"">B3_Qwen2_2B</a>",2.21,unknown,68.1,67.0,61.19,70.85,79.88,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 38 |
+
37,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-3B"">e5-omni-3B</a>",3.0,2026-01-09,67.59,64.72,62.11,70.54,79.62,84.8,76.7,75.1,53.0,29.1,41.7,76.5,66.2,58.6,85.5,64.9,54.8,91.2,52.8,52.7,59.8,43.6,65.4,82.8,53.1,78.9,54.9,74.6,77.7,78.1,72.5,68.4,89.2,19.5,74.9,76.1,81.7,70.9,85.3,75.8,86.5
|
| 39 |
+
38,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-7B</a>",8.03,2025-07-06,67.56,63.63,61.66,69.07,87.58,89.8,83.2,79.9,22.5,16.7,45.0,77.3,78.7,55.2,88.0,67.3,63.8,79.2,53.3,48.8,52.5,65.4,65.7,76.8,43.8,82.7,60.4,69.5,79.4,75.4,73.1,66.7,89.3,39.0,61.2,60.8,71.3,84.7,89.4,83.0,93.2
|
| 40 |
+
39,"<a href=""https://huggingface.co/DeepGlint-AI/UniME-LLaVA-1.6-7B"">UniME(LLaVA-1.6-7B-LoRA-LowRes)</a>",7.57,unknown,66.6,60.6,52.9,67.9,85.1,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 41 |
+
40,"<a href=""https://huggingface.co/zhibinlan/UME-R1-2B"">UME-R1-2B</a>",2.21,2025-10-20,66.56,64.81,62.78,67.62,77.17,80.0,81.1,79.4,52.0,23.4,42.6,75.3,75.2,50.4,88.7,62.4,51.1,92.2,67.7,64.9,54.1,42.7,67.3,78.6,46.8,76.6,53.7,71.7,74.2,75.1,68.9,67.2,90.0,17.1,62.0,66.9,88.0,69.5,83.3,84.4,71.5
|
| 42 |
+
41,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-7B"">VLM2Vec (Qwen2-VL-7B-LoRA-HighRes)</a>",8.29,unknown,65.8,62.6,57.8,69.9,81.7,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 43 |
+
42,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-7B"">VLM2Vec-V1-Qwen2VL-7B</a>",8.29,2025-12-29,65.37,62.76,56.52,69.4,81.9,80.6,79.5,77.3,40.5,30.2,37.2,80.2,70.3,57.6,74.2,56.8,47.5,88.8,59.0,56.6,52.7,38.2,54.4,71.6,39.6,81.6,51.4,80.3,81.2,77.5,73.6,67.5,88.3,16.8,62.1,66.6,85.9,75.4,87.1,84.4,80.7
|
| 44 |
+
43,"<a href=""https://huggingface.co/zhibinlan/LLaVE-2B"">LLaVE-2B</a>",1.95,unknown,65.2,62.1,60.2,65.2,84.9,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 45 |
+
44,"<a href=""https://huggingface.co/VLM2Vec/VLM2Vec-V2.0"">VLM2Vec-V2.0-Qwen2VL-2B</a>",2.21,2025-12-29,64.92,62.93,56.42,69.6,77.12,84.9,73.0,70.9,65.1,25.8,36.1,80.8,55.8,47.6,89.3,51.7,44.0,90.1,59.1,48.1,52.8,38.1,65.4,71.6,43.3,82.7,57.3,74.7,78.3,75.9,71.1,68.4,90.6,19.6,67.6,64.8,84.2,66.2,87.0,86.3,69.0
|
| 46 |
+
45,"<a href=""https://huggingface.co/DeepGlint-AI/UniME-Phi3.5-V-4.2B"">UniME(Phi-3.5-V-LoRA)</a>",4.2,unknown,64.2,54.8,55.9,64.5,81.8,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 47 |
+
46,"<a href=""https://huggingface.co/JUNJIE99/MMRet-large"">MMRet-MLLM (FT)</a>",7.57,unknown,64.1,56.0,57.4,69.9,83.6,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 48 |
+
47,"<a href=""https://huggingface.co/friedrichor/Unite-Instruct-Qwen2-VL-2B"">UNITE-Instruct-2B</a>",2.21,unknown,63.3,63.2,55.9,65.4,75.6,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 49 |
+
48,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-LLaVa-Next"">VLM2Vec (LLaVA-1.6-LoRA-HighRes)</a>",7.57,unknown,62.9,61.2,49.9,67.4,86.1,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 50 |
+
49,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Full"">VLM2Vec (Phi-3.5-V-LoRA)</a>",4.15,unknown,60.1,54.8,54.9,62.3,79.5,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 51 |
+
50,"<a href=""https://huggingface.co/BAAI/BGE-VL-v1.5-zs"">BGE-VL-v1.5 (zeroshot; LlaVA-1.6-Mistral)</a>",7.57,unknown,60.1,56.1,55.3,63.9,70.8,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 52 |
+
51,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-2B"">VLM2Vec-V1-Qwen2VL-2B</a>",2.21,2025-12-29,59.73,58.61,49.16,65.02,73.05,74.3,73.8,73.7,36.9,21.7,35.0,77.5,57.9,50.6,84.7,48.2,39.7,82.7,47.3,42.2,50.9,30.5,48.1,63.2,38.8,75.1,46.8,73.4,73.8,73.1,68.3,65.8,85.8,13.8,54.6,68.4,81.4,65.7,80.8,76.6,69.1
|
| 53 |
+
52,"<a href=""https://arxiv.org/pdf/2503.19900"">interestFM-UIR-CAFe-0.5B</a>",0.894,unknown,59.6,59.1,49.1,61.0,83.0,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 54 |
+
53,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-2B"">VLM2Vec (Qwen2-VL-2B-LoRA-HighRes)</a>",2.21,unknown,59.3,59.0,49.4,65.4,73.4,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 55 |
+
54,"<a href=""https://huggingface.co/zhibinlan/LLaVE-0.5B"">LLaVE-0.5B</a>",0.894,unknown,59.1,57.4,50.3,59.8,82.9,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 56 |
+
55,"<a href=""https://huggingface.co/intfloat/mmE5-mllama-11b-instruct"">mmE5 (w/ 560K synthetic data)</a>",10.6,unknown,58.6,60.6,55.7,54.7,72.4,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 57 |
+
56,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct"">gme-Qwen2-VL-7B-Instruct</a>",8.29,2025-12-29,55.93,57.56,34.57,71.2,59.45,80.1,50.3,69.4,69.0,24.6,39.1,64.7,53.9,40.6,83.9,33.1,20.8,41.1,20.5,17.7,22.2,28.2,76.8,46.4,38.9,60.9,54.9,79.5,83.6,71.5,57.4,67.6,91.3,37.6,78.4,75.6,96.1,31.4,61.2,78.7,66.5
|
| 58 |
+
57,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Full"">VLM2Vec (Phi-3.5-V-FT)</a>",4.15,unknown,55.9,52.8,50.3,57.8,72.3,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 59 |
+
58,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"">gme-Qwen2-VL-2B-Instruct</a>",2.21,unknown,55.8,56.9,41.2,67.8,53.4,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 60 |
+
59,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-0.5B</a>",0.894,2025-07-06,55.43,56.44,45.28,57.55,71.95,81.9,69.6,68.8,51.0,11.3,37.4,64.6,55.3,38.1,86.4,47.1,43.0,60.6,30.2,32.7,48.9,39.7,52.1,59.6,38.9,68.4,43.4,58.4,61.0,66.4,63.2,63.8,80.0,23.3,46.4,52.4,63.9,63.1,76.6,70.6,77.5
|
| 61 |
+
60,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-LLaVa-Next"">VLM2Vec (LLaVA-1.6-LoRA-LowRes)</a>",7.57,unknown,55.0,54.7,50.3,56.2,64.0,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 62 |
+
61,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret"">LamRA-Ret</a>",8.29,2025-12-29,54.13,59.27,26.49,70.06,62.62,80.0,51.6,68.7,66.3,28.3,40.5,72.6,49.1,47.2,88.4,37.9,26.9,22.4,16.5,11.6,19.8,26.5,38.3,33.1,31.9,61.0,52.1,70.9,84.1,72.0,73.6,65.7,81.2,41.7,70.1,82.2,86.1,44.7,62.5,76.2,67.1
|
| 63 |
+
62,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret-Qwen2.5VL-7b"">LamRA-Ret-Qwen2.5VL-7b</a>",8.29,2025-12-29,52.54,51.19,33.31,67.72,58.45,78.2,30.4,64.9,59.2,20.6,35.9,59.2,50.2,36.3,77.0,37.7,31.2,37.9,23.2,14.5,24.4,31.7,55.0,45.5,32.0,63.0,46.6,69.9,75.5,68.0,71.4,65.8,85.7,34.7,66.5,85.0,80.5,38.7,59.1,84.5,51.5
|
| 64 |
+
63,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"">gme-Qwen2-VL-2B-Instruct</a>",2.21,2025-12-29,51.87,54.55,29.84,66.75,55.62,75.8,50.3,67.0,71.2,26.4,36.1,58.1,53.7,28.4,78.5,30.1,18.6,30.0,11.8,13.3,15.6,27.1,75.3,39.5,37.1,47.7,43.1,74.8,77.7,68.3,63.2,67.6,88.8,32.2,73.8,72.1,91.7,28.4,55.8,73.7,64.6
|
| 65 |
+
64,"<a href=""https://huggingface.co/nvidia/MM-Embed"">MM-Embed</a>",8.18,unknown,50.0,48.1,32.3,63.8,57.8,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 66 |
+
65,"<a href=""https://doi.org/10.48550/arXiv.2212.07143"">OpenCLIP-FT</a>",0.428,unknown,47.2,56.0,21.9,55.4,64.1,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 67 |
+
66,"<a href=""https://doi.org/10.48550/arXiv.2103.00020"">CLIP-FT</a>",0.428,unknown,45.4,55.2,19.7,53.2,62.2,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 68 |
+
67,"<a href=""https://huggingface.co/TIGER-Lab/UniIR"">UniIR (CLIP_SF)</a>",0.428,unknown,44.7,44.3,16.2,61.8,65.3,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 69 |
+
68,"<a href=""https://huggingface.co/JUNJIE99/MMRet-large"">MMRet-MLLM (LLaVA-1.6)</a>",7.57,unknown,44.0,47.2,18.4,56.5,62.2,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 70 |
+
69,"<a href=""https://huggingface.co/TIGER-Lab/UniIR"">UniIR (BLIP_FF)</a>",0.247,unknown,42.8,42.1,15.0,60.1,62.2,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 71 |
+
70,"<a href=""https://github.com/mlfoundations/open_clip"">open_clip-ViT-L/14</a>",0.428,unknown,39.7,47.8,10.9,52.3,53.3,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 72 |
+
71,"<a href=""https://huggingface.co/openai/clip-vit-large-patch14"">clip-vit-large-patch14</a>",0.428,unknown,37.8,42.8,9.1,53.0,51.8,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 73 |
+
72,colpali-v1.3,unknown,2025-12-29,34.89,40.45,11.48,48.15,39.75,69.8,25.6,56.2,45.6,6.0,27.7,42.3,50.9,15.2,65.2,9.4,6.4,11.3,5.0,5.7,6.1,16.5,8.1,18.9,27.4,41.1,8.2,50.5,47.7,58.6,50.4,65.4,54.2,5.9,80.5,50.1,65.2,36.5,65.0,1.2,56.3
|
| 74 |
+
73,"<a href=""https://huggingface.co/google/siglip-base-patch16-224"">siglip-base-patch16-224</a>",0.203,unknown,34.8,40.3,8.4,31.6,59.5,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 75 |
+
74,"<a href=""https://github.com/google-deepmind/magiclens"">Magiclens</a>",0.428,unknown,27.8,38.8,8.3,35.4,26.0,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 76 |
+
75,"<a href=""https://huggingface.co/Salesforce/blip2-opt-2.7b"">blip2-opt-2.7b</a>",3.74,unknown,25.2,27.0,4.2,33.9,47.0,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 77 |
+
76,"<a href=""https://huggingface.co/royokong/e5-v"">e5-v</a>",8.36,unknown,13.3,21.8,4.9,11.5,19.0,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-,-
|
| 78 |
+
77,Taichu-UniRetriever-8B,8.77,2026-01-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 79 |
+
78,Taichu-UniRetriever-v1-2B,2.13,2026-01-06,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 80 |
+
79,TCR,8.77,2026-01-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
rankings/image_ranking.jsonl
CHANGED
|
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See raw diff
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rankings/mmeb_ranking.csv
CHANGED
|
@@ -1,25 +1,43 @@
|
|
| 1 |
-
Rank,Models,Model Size(B),Overall,Image-Overall,Video-Overall,Visdoc-Overall
|
| 2 |
-
1,"<a href=""https://
|
| 3 |
-
2,"<a href=""https://
|
| 4 |
-
3,
|
| 5 |
-
4,
|
| 6 |
-
5,"<a href=""https://huggingface.co/
|
| 7 |
-
6,
|
| 8 |
-
7,RzenEmbed-
|
| 9 |
-
8,"<a href=""https://
|
| 10 |
-
9,
|
| 11 |
-
10,"<a href=""https://huggingface.co/
|
| 12 |
-
11,"<a href=""https://
|
| 13 |
-
12,
|
| 14 |
-
13,"<a href=""https://huggingface.co/
|
| 15 |
-
14,
|
| 16 |
-
15,"<a href=""https://huggingface.co/
|
| 17 |
-
16,"<a href=""https://
|
| 18 |
-
17,"<a href=""https://
|
| 19 |
-
18,"<a href=""https://huggingface.co/
|
| 20 |
-
19,"<a href=""https://
|
| 21 |
-
20,"<a href=""https://huggingface.co/
|
| 22 |
-
21,"<a href=""https://
|
| 23 |
-
22,
|
| 24 |
-
23,
|
| 25 |
-
24,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Rank,Models,Model Size(B),Date,Overall,Image-Overall,Video-Overall,Visdoc-Overall
|
| 2 |
+
1,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B"">Qwen3-VL-Embedding-8B</a>",8.14,2026-01-06,79.87,80.12,67.15,83.09
|
| 3 |
+
2,"<a href=""https://console.volcengine.com/ark/region:ark+cn-beijing/model/detail?Id=doubao-embedding-vision"">seed1.6-embedding-1215</a>",unknown,2025-12-18,77.58,77.99,67.74,83.16
|
| 4 |
+
3,WeMM-Embedding-8B,8.77,2025-12-16,76.38,78.09,63.24,82.49
|
| 5 |
+
4,"<a href=""https://interestfm-tte.github.io/"">IFM-TTE-7B</a>",8.29,2025-10-11,76.02,77.9,59.19,83.14
|
| 6 |
+
5,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B"">Qwen3-VL-Embedding-2B</a>",2.13,2026-01-06,75.18,74.96,61.87,80.16
|
| 7 |
+
6,WeMM-Embedding-2B,2.13,2025-12-16,73.56,76.08,58.67,79.85
|
| 8 |
+
7,"<a href=""https://github.com/360CVGroup/RzenEmbed"">RzenEmbed-v2-7B</a>",8.29,2025-09-20,73.5,75.92,55.73,82.31
|
| 9 |
+
8,"<a href=""https://seed1-6-embedding.github.io"">seed-1.6-embedding</a>",unknown,2025-06-17,73.14,77.78,55.34,78.37
|
| 10 |
+
9,RzenEmbed-v1-7B,8.29,2025-07-30,70.69,73.6,48.87,82.0
|
| 11 |
+
10,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-7B"">Ops-MM-embedding-v1-7B</a>",8.29,2025-07-02,69.39,72.72,53.76,74.99
|
| 12 |
+
11,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-7B"">e5-omni-7B</a>",8.0,2026-01-09,68.1,71.23,43.54,81.3
|
| 13 |
+
12,Crotchet-embedding-2B,2.13,2025-12-31,67.3,68.18,50.63,73.59
|
| 14 |
+
13,"<a href=""https://huggingface.co/zhibinlan/UME-R1-7B"">UME-R1-7B</a>",8.29,2025-10-20,66.2,71.25,47.5,71.71
|
| 15 |
+
14,RzenEmbed-v1-2B,2.21,2025-07-16,66.05,68.53,42.62,79.4
|
| 16 |
+
15,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-2B"">Ops-MM-embedding-v1-2B</a>",2.21,2025-07-02,65.11,69.03,47.56,71.48
|
| 17 |
+
16,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-3B"">e5-omni-3B</a>",3.0,2026-01-09,64.74,67.59,40.63,78.11
|
| 18 |
+
17,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-7B</a>",8.03,2025-07-06,62.23,67.56,42.4,68.1
|
| 19 |
+
18,"<a href=""https://huggingface.co/zhibinlan/UME-R1-2B"">UME-R1-2B</a>",2.21,2025-10-20,61.69,66.56,42.23,68.16
|
| 20 |
+
19,"<a href=""https://github.com/GaryGuTC/UniME-v2"">UniME-V2-LLaVA-OneVision-7B</a>",8.03,2025-10-15,61.13,71.77,39.01,60.24
|
| 21 |
+
20,"<a href=""https://huggingface.co/VLM2Vec/VLM2Vec-V2.0"">VLM2Vec-V2.0-Qwen2VL-2B</a>",2.21,2025-12-29,59.01,64.92,34.67,63.56
|
| 22 |
+
21,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct"">gme-Qwen2-VL-7B-Instruct</a>",8.29,2025-12-29,58.83,55.93,38.43,73.96
|
| 23 |
+
22,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"">gme-Qwen2-VL-2B-Instruct</a>",2.21,2025-12-29,55.06,51.87,33.59,71.88
|
| 24 |
+
23,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-0.5B</a>",0.894,2025-07-06,50.99,55.43,35.87,54.83
|
| 25 |
+
24,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-7B"">VLM2Vec-V1-Qwen2VL-7B</a>",8.29,2025-12-29,48.23,65.37,33.79,26.82
|
| 26 |
+
25,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret-Qwen2.5VL-7b"">LamRA-Ret-Qwen2.5VL-7b</a>",8.29,2025-12-29,48.05,52.54,33.83,47.61
|
| 27 |
+
26,colpali-v1.3,unknown,2025-12-29,45.36,34.89,28.23,70.5
|
| 28 |
+
27,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-2B"">VLM2Vec-V1-Qwen2VL-2B</a>",2.21,2025-12-29,43.81,59.73,28.55,26.0
|
| 29 |
+
28,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret"">LamRA-Ret</a>",8.29,2025-12-29,42.7,54.13,35.21,27.72
|
| 30 |
+
29,QQMM-embed-v3,8.29,2025-12-30,37.05,78.21,0.0,0.0
|
| 31 |
+
30,"<a href=""https://github.com/QQ-MM/QQMM-embed"">QQMM-embed-v2</a>",8.29,2025-09-15,35.66,75.28,0.0,0.0
|
| 32 |
+
31,UniVec-CoT-7B,8.29,unknown,35.1,74.11,0.0,0.0
|
| 33 |
+
32,OEmbedding-v1-7B,8.29,2025-10-14,35.08,74.05,0.0,0.0
|
| 34 |
+
33,ReCo-7B,8.29,2025-08-15,34.99,73.87,0.0,0.0
|
| 35 |
+
34,UniVec-7B,8.29,unknown,34.96,73.79,0.0,0.0
|
| 36 |
+
35,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-7B</a>",8.29,2025-11-24,34.91,73.7,0.0,0.0
|
| 37 |
+
36,dp-embedding-v3-lite,8.29,2025-12-15,34.76,73.38,0.0,0.0
|
| 38 |
+
37,TCE-v1,8.0,2025-10-31,34.27,72.36,0.0,0.0
|
| 39 |
+
38,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-3B</a>",3.75,2025-11-24,33.25,70.2,0.0,0.0
|
| 40 |
+
39,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-2B</a>",2.21,2025-11-24,32.78,69.21,0.0,0.0
|
| 41 |
+
40,Taichu-UniRetriever-8B,8.77,2026-01-15,26.29,0.0,0.0,83.72
|
| 42 |
+
41,Taichu-UniRetriever-v1-2B,2.13,2026-01-06,24.21,0.0,0.0,81.93
|
| 43 |
+
42,TCR,8.77,2026-01-15,0.0,0.0,0.0,0.0
|
rankings/mmeb_ranking.jsonl
CHANGED
|
@@ -1,24 +1,42 @@
|
|
| 1 |
-
{"Rank":1,"Models":"<a href=\"https:\/\/
|
| 2 |
-
{"Rank":2,"Models":"<a href=\"https:\/\/
|
| 3 |
-
{"Rank":3,"Models":"
|
| 4 |
-
{"Rank":4,"Models":"
|
| 5 |
-
{"Rank":5,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 6 |
-
{"Rank":6,"Models":"
|
| 7 |
-
{"Rank":7,"Models":"RzenEmbed-
|
| 8 |
-
{"Rank":8,"Models":"<a href=\"https:\/\/
|
| 9 |
-
{"Rank":9,"Models":"
|
| 10 |
-
{"Rank":10,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 11 |
-
{"Rank":11,"Models":"<a href=\"https:\/\/
|
| 12 |
-
{"Rank":12,"Models":"
|
| 13 |
-
{"Rank":13,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 14 |
-
{"Rank":14,"Models":"
|
| 15 |
-
{"Rank":15,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 16 |
-
{"Rank":16,"Models":"<a href=\"https:\/\/
|
| 17 |
-
{"Rank":17,"Models":"<a href=\"https:\/\/
|
| 18 |
-
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 19 |
-
{"Rank":19,"Models":"<a href=\"https:\/\/
|
| 20 |
-
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 21 |
-
{"Rank":21,"Models":"<a href=\"https:\/\/
|
| 22 |
-
{"Rank":22,"Models":"
|
| 23 |
-
{"Rank":23,"Models":"
|
| 24 |
-
{"Rank":24,"Models":"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{"Rank":1,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-8B\">Qwen3-VL-Embedding-8B<\/a>","Model Size(B)":8.14,"Date":"2026-01-06","Overall":79.87,"Image-Overall":80.12,"Video-Overall":67.15,"Visdoc-Overall":83.09}
|
| 2 |
+
{"Rank":2,"Models":"<a href=\"https:\/\/console.volcengine.com\/ark\/region:ark+cn-beijing\/model\/detail?Id=doubao-embedding-vision\">seed1.6-embedding-1215<\/a>","Model Size(B)":"unknown","Date":"2025-12-18","Overall":77.58,"Image-Overall":77.99,"Video-Overall":67.74,"Visdoc-Overall":83.16}
|
| 3 |
+
{"Rank":3,"Models":"WeMM-Embedding-8B","Model Size(B)":8.77,"Date":"2025-12-16","Overall":76.38,"Image-Overall":78.09,"Video-Overall":63.24,"Visdoc-Overall":82.49}
|
| 4 |
+
{"Rank":4,"Models":"<a href=\"https:\/\/interestfm-tte.github.io\/\">IFM-TTE-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-11","Overall":76.02,"Image-Overall":77.9,"Video-Overall":59.19,"Visdoc-Overall":83.14}
|
| 5 |
+
{"Rank":5,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-2B\">Qwen3-VL-Embedding-2B<\/a>","Model Size(B)":2.13,"Date":"2026-01-06","Overall":75.18,"Image-Overall":74.96,"Video-Overall":61.87,"Visdoc-Overall":80.16}
|
| 6 |
+
{"Rank":6,"Models":"WeMM-Embedding-2B","Model Size(B)":2.13,"Date":"2025-12-16","Overall":73.56,"Image-Overall":76.08,"Video-Overall":58.67,"Visdoc-Overall":79.85}
|
| 7 |
+
{"Rank":7,"Models":"<a href=\"https:\/\/github.com\/360CVGroup\/RzenEmbed\">RzenEmbed-v2-7B<\/a>","Model Size(B)":8.29,"Date":"2025-09-20","Overall":73.5,"Image-Overall":75.92,"Video-Overall":55.73,"Visdoc-Overall":82.31}
|
| 8 |
+
{"Rank":8,"Models":"<a href=\"https:\/\/seed1-6-embedding.github.io\">seed-1.6-embedding<\/a>","Model Size(B)":"unknown","Date":"2025-06-17","Overall":73.14,"Image-Overall":77.78,"Video-Overall":55.34,"Visdoc-Overall":78.37}
|
| 9 |
+
{"Rank":9,"Models":"RzenEmbed-v1-7B","Model Size(B)":8.29,"Date":"2025-07-30","Overall":70.69,"Image-Overall":73.6,"Video-Overall":48.87,"Visdoc-Overall":82.0}
|
| 10 |
+
{"Rank":10,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-7B\">Ops-MM-embedding-v1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-07-02","Overall":69.39,"Image-Overall":72.72,"Video-Overall":53.76,"Visdoc-Overall":74.99}
|
| 11 |
+
{"Rank":11,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-7B\">e5-omni-7B<\/a>","Model Size(B)":8.0,"Date":"2026-01-09","Overall":68.1,"Image-Overall":71.23,"Video-Overall":43.54,"Visdoc-Overall":81.3}
|
| 12 |
+
{"Rank":12,"Models":"Crotchet-embedding-2B","Model Size(B)":2.13,"Date":"2025-12-31","Overall":67.3,"Image-Overall":68.18,"Video-Overall":50.63,"Visdoc-Overall":73.59}
|
| 13 |
+
{"Rank":13,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-7B\">UME-R1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-20","Overall":66.2,"Image-Overall":71.25,"Video-Overall":47.5,"Visdoc-Overall":71.71}
|
| 14 |
+
{"Rank":14,"Models":"RzenEmbed-v1-2B","Model Size(B)":2.21,"Date":"2025-07-16","Overall":66.05,"Image-Overall":68.53,"Video-Overall":42.62,"Visdoc-Overall":79.4}
|
| 15 |
+
{"Rank":15,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-2B\">Ops-MM-embedding-v1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-07-02","Overall":65.11,"Image-Overall":69.03,"Video-Overall":47.56,"Visdoc-Overall":71.48}
|
| 16 |
+
{"Rank":16,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-3B\">e5-omni-3B<\/a>","Model Size(B)":3.0,"Date":"2026-01-09","Overall":64.74,"Image-Overall":67.59,"Video-Overall":40.63,"Visdoc-Overall":78.11}
|
| 17 |
+
{"Rank":17,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-7B<\/a>","Model Size(B)":8.03,"Date":"2025-07-06","Overall":62.23,"Image-Overall":67.56,"Video-Overall":42.4,"Visdoc-Overall":68.1}
|
| 18 |
+
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-2B\">UME-R1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-10-20","Overall":61.69,"Image-Overall":66.56,"Video-Overall":42.23,"Visdoc-Overall":68.16}
|
| 19 |
+
{"Rank":19,"Models":"<a href=\"https:\/\/github.com\/GaryGuTC\/UniME-v2\">UniME-V2-LLaVA-OneVision-7B<\/a>","Model Size(B)":8.03,"Date":"2025-10-15","Overall":61.13,"Image-Overall":71.77,"Video-Overall":39.01,"Visdoc-Overall":60.24}
|
| 20 |
+
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/VLM2Vec\/VLM2Vec-V2.0\">VLM2Vec-V2.0-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Overall":59.01,"Image-Overall":64.92,"Video-Overall":34.67,"Visdoc-Overall":63.56}
|
| 21 |
+
{"Rank":21,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-7B-Instruct\">gme-Qwen2-VL-7B-Instruct<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Overall":58.83,"Image-Overall":55.93,"Video-Overall":38.43,"Visdoc-Overall":73.96}
|
| 22 |
+
{"Rank":22,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-2B-Instruct\">gme-Qwen2-VL-2B-Instruct<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Overall":55.06,"Image-Overall":51.87,"Video-Overall":33.59,"Visdoc-Overall":71.88}
|
| 23 |
+
{"Rank":23,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-0.5B<\/a>","Model Size(B)":0.894,"Date":"2025-07-06","Overall":50.99,"Image-Overall":55.43,"Video-Overall":35.87,"Visdoc-Overall":54.83}
|
| 24 |
+
{"Rank":24,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-7B\">VLM2Vec-V1-Qwen2VL-7B<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Overall":48.23,"Image-Overall":65.37,"Video-Overall":33.79,"Visdoc-Overall":26.82}
|
| 25 |
+
{"Rank":25,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret-Qwen2.5VL-7b\">LamRA-Ret-Qwen2.5VL-7b<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Overall":48.05,"Image-Overall":52.54,"Video-Overall":33.83,"Visdoc-Overall":47.61}
|
| 26 |
+
{"Rank":26,"Models":"colpali-v1.3","Model Size(B)":"unknown","Date":"2025-12-29","Overall":45.36,"Image-Overall":34.89,"Video-Overall":28.23,"Visdoc-Overall":70.5}
|
| 27 |
+
{"Rank":27,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-2B\">VLM2Vec-V1-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Overall":43.81,"Image-Overall":59.73,"Video-Overall":28.55,"Visdoc-Overall":26.0}
|
| 28 |
+
{"Rank":28,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret\">LamRA-Ret<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Overall":42.7,"Image-Overall":54.13,"Video-Overall":35.21,"Visdoc-Overall":27.72}
|
| 29 |
+
{"Rank":29,"Models":"QQMM-embed-v3","Model Size(B)":8.29,"Date":"2025-12-30","Overall":37.05,"Image-Overall":78.21,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 30 |
+
{"Rank":30,"Models":"<a href=\"https:\/\/github.com\/QQ-MM\/QQMM-embed\">QQMM-embed-v2<\/a>","Model Size(B)":8.29,"Date":"2025-09-15","Overall":35.66,"Image-Overall":75.28,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 31 |
+
{"Rank":31,"Models":"UniVec-CoT-7B","Model Size(B)":8.29,"Date":"unknown","Overall":35.1,"Image-Overall":74.11,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 32 |
+
{"Rank":32,"Models":"OEmbedding-v1-7B","Model Size(B)":8.29,"Date":"2025-10-14","Overall":35.08,"Image-Overall":74.05,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 33 |
+
{"Rank":33,"Models":"ReCo-7B","Model Size(B)":8.29,"Date":"2025-08-15","Overall":34.99,"Image-Overall":73.87,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 34 |
+
{"Rank":34,"Models":"UniVec-7B","Model Size(B)":8.29,"Date":"unknown","Overall":34.96,"Image-Overall":73.79,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 35 |
+
{"Rank":35,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-7B<\/a>","Model Size(B)":8.29,"Date":"2025-11-24","Overall":34.91,"Image-Overall":73.7,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 36 |
+
{"Rank":36,"Models":"dp-embedding-v3-lite","Model Size(B)":8.29,"Date":"2025-12-15","Overall":34.76,"Image-Overall":73.38,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 37 |
+
{"Rank":37,"Models":"TCE-v1","Model Size(B)":8.0,"Date":"2025-10-31","Overall":34.27,"Image-Overall":72.36,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 38 |
+
{"Rank":38,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-3B<\/a>","Model Size(B)":3.75,"Date":"2025-11-24","Overall":33.25,"Image-Overall":70.2,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 39 |
+
{"Rank":39,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-2B<\/a>","Model Size(B)":2.21,"Date":"2025-11-24","Overall":32.78,"Image-Overall":69.21,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
| 40 |
+
{"Rank":40,"Models":"Taichu-UniRetriever-8B","Model Size(B)":8.77,"Date":"2026-01-15","Overall":26.29,"Image-Overall":0.0,"Video-Overall":0.0,"Visdoc-Overall":83.72}
|
| 41 |
+
{"Rank":41,"Models":"Taichu-UniRetriever-v1-2B","Model Size(B)":2.13,"Date":"2026-01-06","Overall":24.21,"Image-Overall":0.0,"Video-Overall":0.0,"Visdoc-Overall":81.93}
|
| 42 |
+
{"Rank":42,"Models":"TCR","Model Size(B)":8.77,"Date":"2026-01-15","Overall":0.0,"Image-Overall":0.0,"Video-Overall":0.0,"Visdoc-Overall":0.0}
|
rankings/video_ranking.csv
CHANGED
|
@@ -1,25 +1,43 @@
|
|
| 1 |
-
Rank,Models,Model Size(B),Video-Overall,V-CLS,V-QA,V-RET,V-MRET,K700,UCF101,HMDB51,SmthSmthV2,Breakfast,Video-MME,MVBench,NExTQA,EgoSchema,ActivityNetQA,MSR-VTT,MSVD,DiDeMo,VATEX,YouCook2,QVHighlight,Charades-STA,MomentSeeker
|
| 2 |
-
1,"<a href=""https://
|
| 3 |
-
2,"<a href=""https://
|
| 4 |
-
3,
|
| 5 |
-
4,"<a href=""https://huggingface.co/
|
| 6 |
-
5,
|
| 7 |
-
6,
|
| 8 |
-
7,"<a href=""https://
|
| 9 |
-
8,
|
| 10 |
-
9,"<a href=""https://
|
| 11 |
-
10,
|
| 12 |
-
11,
|
| 13 |
-
12,"<a href=""https://huggingface.co/
|
| 14 |
-
13,"<a href=""https://
|
| 15 |
-
14,"<a href=""https://huggingface.co/
|
| 16 |
-
15,
|
| 17 |
-
16,"<a href=""https://
|
| 18 |
-
17,"<a href=""https://huggingface.co/
|
| 19 |
-
18,"<a href=""https://huggingface.co/
|
| 20 |
-
19,"<a href=""https://
|
| 21 |
-
20,"<a href=""https://huggingface.co/
|
| 22 |
-
21,"<a href=""https://
|
| 23 |
-
22,
|
| 24 |
-
23,
|
| 25 |
-
24,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Rank,Models,Model Size(B),Date,Video-Overall,V-CLS,V-QA,V-RET,V-MRET,K700,UCF101,HMDB51,SmthSmthV2,Breakfast,Video-MME,MVBench,NExTQA,EgoSchema,ActivityNetQA,MSR-VTT,MSVD,DiDeMo,VATEX,YouCook2,QVHighlight,Charades-STA,MomentSeeker
|
| 2 |
+
1,"<a href=""https://console.volcengine.com/ark/region:ark+cn-beijing/model/detail?Id=doubao-embedding-vision"">seed1.6-embedding-1215</a>",unknown,2025-12-18,67.74,85.19,66.71,59.09,54.79,76.0,98.7,93.5,94.7,63.05,54.67,56.35,78.61,58.0,85.9,60.2,74.48,66.43,54.87,39.48,75.25,33.43,55.68
|
| 3 |
+
2,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B"">Qwen3-VL-Embedding-8B</a>",8.14,2026-01-06,67.15,78.39,70.96,58.73,56.09,67.6,95.1,83.4,81.2,64.67,62.63,66.9,76.19,69.0,80.1,58.2,75.67,66.04,54.87,38.85,79.22,34.11,54.93
|
| 4 |
+
3,WeMM-Embedding-8B,8.77,2025-12-16,63.24,66.47,71.66,56.43,55.16,65.1,84.2,61.5,73.3,48.27,66.63,66.88,79.58,66.8,78.4,55.3,73.43,69.22,55.05,29.16,80.98,32.74,51.75
|
| 5 |
+
4,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B"">Qwen3-VL-Embedding-2B</a>",2.13,2026-01-06,61.87,71.94,64.94,53.88,53.26,61.9,91.8,78.7,72.8,54.5,56.96,59.65,72.01,60.6,75.5,53.8,75.07,57.87,49.11,33.56,76.92,29.99,52.87
|
| 6 |
+
5,"<a href=""https://interestfm-tte.github.io/"">IFM-TTE-7B</a>",8.29,2025-10-11,59.19,60.53,67.92,51.73,54.86,57.4,79.6,65.4,62.6,37.64,59.67,62.85,73.76,65.8,77.5,52.7,73.13,49.7,51.45,31.65,64.64,50.34,49.61
|
| 7 |
+
6,WeMM-Embedding-2B,2.13,2025-12-16,58.67,61.5,64.03,54.15,52.55,58.9,75.1,57.7,63.4,52.42,58.19,61.35,73.82,51.0,75.8,53.1,73.43,65.24,52.52,26.45,79.69,28.2,49.75
|
| 8 |
+
7,"<a href=""https://github.com/360CVGroup/RzenEmbed"">RzenEmbed-v2-7B</a>",8.29,2025-09-20,55.73,58.82,63.5,50.97,45.54,57.1,75.7,63.4,66.5,31.41,51.48,60.3,75.91,51.2,78.6,50.6,72.09,57.27,47.57,27.34,64.27,24.62,47.72
|
| 9 |
+
8,"<a href=""https://seed1-6-embedding.github.io"">seed-1.6-embedding</a>",unknown,2025-06-17,55.34,54.99,60.85,51.33,53.45,48.0,74.2,63.9,61.6,27.25,53.96,53.27,66.2,52.2,78.6,55.3,71.34,56.67,48.77,24.57,71.75,29.3,59.3
|
| 10 |
+
9,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-7B"">Ops-MM-embedding-v1-7B</a>",8.29,2025-07-02,53.76,59.68,62.22,45.72,43.21,59.0,78.8,59.3,64.6,36.72,50.89,56.97,67.06,59.6,76.6,49.4,67.16,46.12,43.95,21.96,58.17,24.9,46.56
|
| 11 |
+
10,Crotchet-embedding-2B,2.13,2025-12-31,50.63,53.78,55.82,43.44,48.69,52.2,75.7,49.5,53.6,37.88,46.56,50.88,53.07,54.0,74.6,44.9,65.97,44.52,40.35,21.45,70.54,26.41,49.13
|
| 12 |
+
11,RzenEmbed-v1-7B,8.29,2025-07-30,48.87,52.76,56.18,41.89,41.82,55.4,73.1,56.7,56.9,21.71,48.67,48.58,66.77,42.8,74.1,45.1,64.93,41.24,38.57,19.6,60.2,22.15,43.11
|
| 13 |
+
12,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-2B"">Ops-MM-embedding-v1-2B</a>",2.21,2025-07-02,47.56,53.61,55.65,41.75,33.68,52.0,71.4,55.5,58.9,30.25,44.63,50.75,57.26,53.8,71.8,46.0,66.12,39.84,40.24,16.55,39.52,19.53,42.0
|
| 14 |
+
13,"<a href=""https://huggingface.co/zhibinlan/UME-R1-7B"">UME-R1-7B</a>",8.29,2025-10-20,47.5,48.6,60.7,38.16,39.26,42.8,70.0,58.3,50.4,21.48,47.26,58.2,69.62,52.4,76.0,38.9,60.75,40.04,32.65,18.46,54.85,21.87,41.06
|
| 15 |
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14,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-7B"">e5-omni-7B</a>",8.0,2026-01-09,43.54,46.61,52.94,36.67,34.19,48.0,66.0,54.4,41.3,23.33,45.59,50.3,62.11,39.0,67.7,42.1,57.16,36.06,33.54,14.47,42.38,17.88,42.32
|
| 16 |
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15,RzenEmbed-v1-2B,2.21,2025-07-16,42.62,45.56,47.54,38.32,36.69,46.4,69.9,48.9,49.9,12.7,39.78,41.58,49.53,35.6,71.2,43.0,58.36,39.54,33.79,16.89,51.52,18.16,40.39
|
| 17 |
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16,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-7B</a>",8.03,2025-07-06,42.4,35.81,58.66,34.44,39.53,40.1,39.6,46.9,35.8,16.63,46.0,48.9,62.42,60.0,76.0,36.5,56.42,37.85,31.96,9.47,58.45,18.71,41.44
|
| 18 |
+
17,"<a href=""https://huggingface.co/zhibinlan/UME-R1-2B"">UME-R1-2B</a>",2.21,2025-10-20,42.23,44.32,50.95,32.93,39.7,35.8,67.2,54.4,44.1,20.09,41.67,49.88,59.98,45.4,57.8,34.3,55.37,32.37,29.88,12.71,57.53,20.36,41.22
|
| 19 |
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18,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-3B"">e5-omni-3B</a>",3.0,2026-01-09,40.63,40.2,48.54,33.14,40.67,41.9,58.0,42.2,34.4,24.48,43.63,45.32,54.37,36.6,62.8,36.0,52.69,34.76,28.58,13.68,62.6,18.16,41.26
|
| 20 |
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19,"<a href=""https://github.com/GaryGuTC/UniME-v2"">UniME-V2-LLaVA-OneVision-7B</a>",8.03,2025-10-15,39.01,37.16,50.59,28.93,39.59,38.0,61.8,42.8,25.2,18.01,35.78,42.2,58.76,51.6,64.6,27.6,57.46,31.47,22.51,5.6,56.79,29.99,32.0
|
| 21 |
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20,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct"">gme-Qwen2-VL-7B-Instruct</a>",8.29,2025-12-29,38.43,37.27,50.28,28.26,37.53,39.6,54.4,48.0,30.5,13.86,39.19,46.3,53.51,46.4,66.0,31.8,49.55,26.29,24.74,8.93,59.37,13.89,39.33
|
| 22 |
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21,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-0.5B</a>",0.894,2025-07-06,35.87,33.9,41.72,29.69,39.69,33.6,47.2,40.5,25.8,22.4,36.11,39.35,38.36,26.2,68.6,33.0,51.19,30.48,25.48,8.3,56.14,23.11,39.83
|
| 23 |
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22,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret"">LamRA-Ret</a>",8.29,2025-12-29,35.21,39.41,42.74,24.47,33.58,42.3,60.7,40.4,36.1,17.55,34.07,37.33,43.69,44.8,53.8,22.6,46.42,25.0,19.09,9.25,53.92,10.87,35.96
|
| 24 |
+
23,"<a href=""https://huggingface.co/VLM2Vec/VLM2Vec-V2.0"">VLM2Vec-V2.0-Qwen2VL-2B</a>",2.21,2025-12-29,34.67,39.24,34.66,28.37,37.55,38.2,60.0,40.2,43.0,14.78,30.81,33.62,20.88,35.0,53.0,27.8,47.31,29.98,26.15,10.63,49.68,20.08,42.88
|
| 25 |
+
24,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret-Qwen2.5VL-7b"">LamRA-Ret-Qwen2.5VL-7b</a>",8.29,2025-12-29,33.83,32.61,42.7,23.68,37.97,32.2,51.1,34.4,25.5,19.86,35.33,37.5,44.99,47.2,48.5,25.9,42.84,23.71,18.29,7.64,61.59,18.98,33.33
|
| 26 |
+
25,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-7B"">VLM2Vec-V1-Qwen2VL-7B</a>",8.29,2025-12-29,33.79,38.99,30.09,29.08,39.16,35.4,62.1,41.9,32.0,23.56,28.04,28.55,20.28,22.2,51.4,34.7,46.72,29.58,25.37,9.03,57.89,18.57,41.01
|
| 27 |
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26,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"">gme-Qwen2-VL-2B-Instruct</a>",2.21,2025-12-29,33.59,34.75,41.75,25.35,31.8,34.9,52.1,43.0,30.1,13.63,33.96,37.57,39.4,40.6,57.2,27.0,47.31,21.51,23.05,7.9,43.95,14.31,37.14
|
| 28 |
+
27,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-2B"">VLM2Vec-V1-Qwen2VL-2B</a>",2.21,2025-12-29,28.55,33.27,30.66,20.45,30.66,31.0,57.6,34.0,30.8,12.93,27.07,30.53,20.2,25.6,49.9,25.6,37.46,19.12,15.68,4.37,43.67,12.93,35.39
|
| 29 |
+
28,colpali-v1.3,unknown,2025-12-29,28.23,26.63,37.82,21.48,26.16,23.3,49.3,24.8,24.9,10.85,30.59,33.58,35.15,38.4,51.4,17.7,45.37,22.51,16.68,5.16,20.13,29.02,29.34
|
| 30 |
+
29,QQMM-embed-v3,8.29,2025-12-30,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 31 |
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30,"<a href=""https://github.com/QQ-MM/QQMM-embed"">QQMM-embed-v2</a>",8.29,2025-09-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 32 |
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31,UniVec-CoT-7B,8.29,unknown,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 33 |
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32,OEmbedding-v1-7B,8.29,2025-10-14,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 34 |
+
33,ReCo-7B,8.29,2025-08-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 35 |
+
34,UniVec-7B,8.29,unknown,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 36 |
+
35,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-7B</a>",8.29,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 37 |
+
36,dp-embedding-v3-lite,8.29,2025-12-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 38 |
+
37,TCE-v1,8.0,2025-10-31,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 39 |
+
38,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-3B</a>",3.75,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 40 |
+
39,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-2B</a>",2.21,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 41 |
+
40,Taichu-UniRetriever-8B,8.77,2026-01-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 42 |
+
41,Taichu-UniRetriever-v1-2B,2.13,2026-01-06,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
| 43 |
+
42,TCR,8.77,2026-01-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
|
rankings/video_ranking.jsonl
CHANGED
|
@@ -1,24 +1,42 @@
|
|
| 1 |
-
{"Rank":1,"Models":"<a href=\"https:\/\/
|
| 2 |
-
{"Rank":2,"Models":"<a href=\"https:\/\/
|
| 3 |
-
{"Rank":3,"Models":"
|
| 4 |
-
{"Rank":4,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 5 |
-
{"Rank":5,"Models":"
|
| 6 |
-
{"Rank":6,"Models":"
|
| 7 |
-
{"Rank":7,"Models":"<a href=\"https:\/\/
|
| 8 |
-
{"Rank":8,"Models":"
|
| 9 |
-
{"Rank":9,"Models":"<a href=\"https:\/\/
|
| 10 |
-
{"Rank":10,"Models":"
|
| 11 |
-
{"Rank":11,"Models":"
|
| 12 |
-
{"Rank":12,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 13 |
-
{"Rank":13,"Models":"<a href=\"https:\/\/
|
| 14 |
-
{"Rank":14,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 15 |
-
{"Rank":15,"Models":"
|
| 16 |
-
{"Rank":16,"Models":"<a href=\"https:\/\/
|
| 17 |
-
{"Rank":17,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 18 |
-
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 19 |
-
{"Rank":19,"Models":"<a href=\"https:\/\/
|
| 20 |
-
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 21 |
-
{"Rank":21,"Models":"<a href=\"https:\/\/
|
| 22 |
-
{"Rank":22,"Models":"
|
| 23 |
-
{"Rank":23,"Models":"
|
| 24 |
-
{"Rank":24,"Models":"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
|
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|
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|
|
|
|
|
| 1 |
+
{"Rank":1,"Models":"<a href=\"https:\/\/console.volcengine.com\/ark\/region:ark+cn-beijing\/model\/detail?Id=doubao-embedding-vision\">seed1.6-embedding-1215<\/a>","Model Size(B)":"unknown","Date":"2025-12-18","Video-Overall":67.74,"V-CLS":85.19,"V-QA":66.71,"V-RET":59.09,"V-MRET":54.79,"K700":76.0,"UCF101":98.7,"HMDB51":93.5,"SmthSmthV2":94.7,"Breakfast":63.05,"Video-MME":54.67,"MVBench":56.35,"NExTQA":78.61,"EgoSchema":58.0,"ActivityNetQA":85.9,"MSR-VTT":60.2,"MSVD":74.48,"DiDeMo":66.43,"VATEX":54.87,"YouCook2":39.48,"QVHighlight":75.25,"Charades-STA":33.43,"MomentSeeker":55.68}
|
| 2 |
+
{"Rank":2,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-8B\">Qwen3-VL-Embedding-8B<\/a>","Model Size(B)":8.14,"Date":"2026-01-06","Video-Overall":67.15,"V-CLS":78.39,"V-QA":70.96,"V-RET":58.73,"V-MRET":56.09,"K700":67.6,"UCF101":95.1,"HMDB51":83.4,"SmthSmthV2":81.2,"Breakfast":64.67,"Video-MME":62.63,"MVBench":66.9,"NExTQA":76.19,"EgoSchema":69.0,"ActivityNetQA":80.1,"MSR-VTT":58.2,"MSVD":75.67,"DiDeMo":66.04,"VATEX":54.87,"YouCook2":38.85,"QVHighlight":79.22,"Charades-STA":34.11,"MomentSeeker":54.93}
|
| 3 |
+
{"Rank":3,"Models":"WeMM-Embedding-8B","Model Size(B)":8.77,"Date":"2025-12-16","Video-Overall":63.24,"V-CLS":66.47,"V-QA":71.66,"V-RET":56.43,"V-MRET":55.16,"K700":65.1,"UCF101":84.2,"HMDB51":61.5,"SmthSmthV2":73.3,"Breakfast":48.27,"Video-MME":66.63,"MVBench":66.88,"NExTQA":79.58,"EgoSchema":66.8,"ActivityNetQA":78.4,"MSR-VTT":55.3,"MSVD":73.43,"DiDeMo":69.22,"VATEX":55.05,"YouCook2":29.16,"QVHighlight":80.98,"Charades-STA":32.74,"MomentSeeker":51.75}
|
| 4 |
+
{"Rank":4,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-2B\">Qwen3-VL-Embedding-2B<\/a>","Model Size(B)":2.13,"Date":"2026-01-06","Video-Overall":61.87,"V-CLS":71.94,"V-QA":64.94,"V-RET":53.88,"V-MRET":53.26,"K700":61.9,"UCF101":91.8,"HMDB51":78.7,"SmthSmthV2":72.8,"Breakfast":54.5,"Video-MME":56.96,"MVBench":59.65,"NExTQA":72.01,"EgoSchema":60.6,"ActivityNetQA":75.5,"MSR-VTT":53.8,"MSVD":75.07,"DiDeMo":57.87,"VATEX":49.11,"YouCook2":33.56,"QVHighlight":76.92,"Charades-STA":29.99,"MomentSeeker":52.87}
|
| 5 |
+
{"Rank":5,"Models":"<a href=\"https:\/\/interestfm-tte.github.io\/\">IFM-TTE-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-11","Video-Overall":59.19,"V-CLS":60.53,"V-QA":67.92,"V-RET":51.73,"V-MRET":54.86,"K700":57.4,"UCF101":79.6,"HMDB51":65.4,"SmthSmthV2":62.6,"Breakfast":37.64,"Video-MME":59.67,"MVBench":62.85,"NExTQA":73.76,"EgoSchema":65.8,"ActivityNetQA":77.5,"MSR-VTT":52.7,"MSVD":73.13,"DiDeMo":49.7,"VATEX":51.45,"YouCook2":31.65,"QVHighlight":64.64,"Charades-STA":50.34,"MomentSeeker":49.61}
|
| 6 |
+
{"Rank":6,"Models":"WeMM-Embedding-2B","Model Size(B)":2.13,"Date":"2025-12-16","Video-Overall":58.67,"V-CLS":61.5,"V-QA":64.03,"V-RET":54.15,"V-MRET":52.55,"K700":58.9,"UCF101":75.1,"HMDB51":57.7,"SmthSmthV2":63.4,"Breakfast":52.42,"Video-MME":58.19,"MVBench":61.35,"NExTQA":73.82,"EgoSchema":51.0,"ActivityNetQA":75.8,"MSR-VTT":53.1,"MSVD":73.43,"DiDeMo":65.24,"VATEX":52.52,"YouCook2":26.45,"QVHighlight":79.69,"Charades-STA":28.2,"MomentSeeker":49.75}
|
| 7 |
+
{"Rank":7,"Models":"<a href=\"https:\/\/github.com\/360CVGroup\/RzenEmbed\">RzenEmbed-v2-7B<\/a>","Model Size(B)":8.29,"Date":"2025-09-20","Video-Overall":55.73,"V-CLS":58.82,"V-QA":63.5,"V-RET":50.97,"V-MRET":45.54,"K700":57.1,"UCF101":75.7,"HMDB51":63.4,"SmthSmthV2":66.5,"Breakfast":31.41,"Video-MME":51.48,"MVBench":60.3,"NExTQA":75.91,"EgoSchema":51.2,"ActivityNetQA":78.6,"MSR-VTT":50.6,"MSVD":72.09,"DiDeMo":57.27,"VATEX":47.57,"YouCook2":27.34,"QVHighlight":64.27,"Charades-STA":24.62,"MomentSeeker":47.72}
|
| 8 |
+
{"Rank":8,"Models":"<a href=\"https:\/\/seed1-6-embedding.github.io\">seed-1.6-embedding<\/a>","Model Size(B)":"unknown","Date":"2025-06-17","Video-Overall":55.34,"V-CLS":54.99,"V-QA":60.85,"V-RET":51.33,"V-MRET":53.45,"K700":48.0,"UCF101":74.2,"HMDB51":63.9,"SmthSmthV2":61.6,"Breakfast":27.25,"Video-MME":53.96,"MVBench":53.27,"NExTQA":66.2,"EgoSchema":52.2,"ActivityNetQA":78.6,"MSR-VTT":55.3,"MSVD":71.34,"DiDeMo":56.67,"VATEX":48.77,"YouCook2":24.57,"QVHighlight":71.75,"Charades-STA":29.3,"MomentSeeker":59.3}
|
| 9 |
+
{"Rank":9,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-7B\">Ops-MM-embedding-v1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-07-02","Video-Overall":53.76,"V-CLS":59.68,"V-QA":62.22,"V-RET":45.72,"V-MRET":43.21,"K700":59.0,"UCF101":78.8,"HMDB51":59.3,"SmthSmthV2":64.6,"Breakfast":36.72,"Video-MME":50.89,"MVBench":56.97,"NExTQA":67.06,"EgoSchema":59.6,"ActivityNetQA":76.6,"MSR-VTT":49.4,"MSVD":67.16,"DiDeMo":46.12,"VATEX":43.95,"YouCook2":21.96,"QVHighlight":58.17,"Charades-STA":24.9,"MomentSeeker":46.56}
|
| 10 |
+
{"Rank":10,"Models":"Crotchet-embedding-2B","Model Size(B)":2.13,"Date":"2025-12-31","Video-Overall":50.63,"V-CLS":53.78,"V-QA":55.82,"V-RET":43.44,"V-MRET":48.69,"K700":52.2,"UCF101":75.7,"HMDB51":49.5,"SmthSmthV2":53.6,"Breakfast":37.88,"Video-MME":46.56,"MVBench":50.88,"NExTQA":53.07,"EgoSchema":54.0,"ActivityNetQA":74.6,"MSR-VTT":44.9,"MSVD":65.97,"DiDeMo":44.52,"VATEX":40.35,"YouCook2":21.45,"QVHighlight":70.54,"Charades-STA":26.41,"MomentSeeker":49.13}
|
| 11 |
+
{"Rank":11,"Models":"RzenEmbed-v1-7B","Model Size(B)":8.29,"Date":"2025-07-30","Video-Overall":48.87,"V-CLS":52.76,"V-QA":56.18,"V-RET":41.89,"V-MRET":41.82,"K700":55.4,"UCF101":73.1,"HMDB51":56.7,"SmthSmthV2":56.9,"Breakfast":21.71,"Video-MME":48.67,"MVBench":48.58,"NExTQA":66.77,"EgoSchema":42.8,"ActivityNetQA":74.1,"MSR-VTT":45.1,"MSVD":64.93,"DiDeMo":41.24,"VATEX":38.57,"YouCook2":19.6,"QVHighlight":60.2,"Charades-STA":22.15,"MomentSeeker":43.11}
|
| 12 |
+
{"Rank":12,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-2B\">Ops-MM-embedding-v1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-07-02","Video-Overall":47.56,"V-CLS":53.61,"V-QA":55.65,"V-RET":41.75,"V-MRET":33.68,"K700":52.0,"UCF101":71.4,"HMDB51":55.5,"SmthSmthV2":58.9,"Breakfast":30.25,"Video-MME":44.63,"MVBench":50.75,"NExTQA":57.26,"EgoSchema":53.8,"ActivityNetQA":71.8,"MSR-VTT":46.0,"MSVD":66.12,"DiDeMo":39.84,"VATEX":40.24,"YouCook2":16.55,"QVHighlight":39.52,"Charades-STA":19.53,"MomentSeeker":42.0}
|
| 13 |
+
{"Rank":13,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-7B\">UME-R1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-20","Video-Overall":47.5,"V-CLS":48.6,"V-QA":60.7,"V-RET":38.16,"V-MRET":39.26,"K700":42.8,"UCF101":70.0,"HMDB51":58.3,"SmthSmthV2":50.4,"Breakfast":21.48,"Video-MME":47.26,"MVBench":58.2,"NExTQA":69.62,"EgoSchema":52.4,"ActivityNetQA":76.0,"MSR-VTT":38.9,"MSVD":60.75,"DiDeMo":40.04,"VATEX":32.65,"YouCook2":18.46,"QVHighlight":54.85,"Charades-STA":21.87,"MomentSeeker":41.06}
|
| 14 |
+
{"Rank":14,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-7B\">e5-omni-7B<\/a>","Model Size(B)":8.0,"Date":"2026-01-09","Video-Overall":43.54,"V-CLS":46.61,"V-QA":52.94,"V-RET":36.67,"V-MRET":34.19,"K700":48.0,"UCF101":66.0,"HMDB51":54.4,"SmthSmthV2":41.3,"Breakfast":23.33,"Video-MME":45.59,"MVBench":50.3,"NExTQA":62.11,"EgoSchema":39.0,"ActivityNetQA":67.7,"MSR-VTT":42.1,"MSVD":57.16,"DiDeMo":36.06,"VATEX":33.54,"YouCook2":14.47,"QVHighlight":42.38,"Charades-STA":17.88,"MomentSeeker":42.32}
|
| 15 |
+
{"Rank":15,"Models":"RzenEmbed-v1-2B","Model Size(B)":2.21,"Date":"2025-07-16","Video-Overall":42.62,"V-CLS":45.56,"V-QA":47.54,"V-RET":38.32,"V-MRET":36.69,"K700":46.4,"UCF101":69.9,"HMDB51":48.9,"SmthSmthV2":49.9,"Breakfast":12.7,"Video-MME":39.78,"MVBench":41.58,"NExTQA":49.53,"EgoSchema":35.6,"ActivityNetQA":71.2,"MSR-VTT":43.0,"MSVD":58.36,"DiDeMo":39.54,"VATEX":33.79,"YouCook2":16.89,"QVHighlight":51.52,"Charades-STA":18.16,"MomentSeeker":40.39}
|
| 16 |
+
{"Rank":16,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-7B<\/a>","Model Size(B)":8.03,"Date":"2025-07-06","Video-Overall":42.4,"V-CLS":35.81,"V-QA":58.66,"V-RET":34.44,"V-MRET":39.53,"K700":40.1,"UCF101":39.6,"HMDB51":46.9,"SmthSmthV2":35.8,"Breakfast":16.63,"Video-MME":46.0,"MVBench":48.9,"NExTQA":62.42,"EgoSchema":60.0,"ActivityNetQA":76.0,"MSR-VTT":36.5,"MSVD":56.42,"DiDeMo":37.85,"VATEX":31.96,"YouCook2":9.47,"QVHighlight":58.45,"Charades-STA":18.71,"MomentSeeker":41.44}
|
| 17 |
+
{"Rank":17,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-2B\">UME-R1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-10-20","Video-Overall":42.23,"V-CLS":44.32,"V-QA":50.95,"V-RET":32.93,"V-MRET":39.7,"K700":35.8,"UCF101":67.2,"HMDB51":54.4,"SmthSmthV2":44.1,"Breakfast":20.09,"Video-MME":41.67,"MVBench":49.88,"NExTQA":59.98,"EgoSchema":45.4,"ActivityNetQA":57.8,"MSR-VTT":34.3,"MSVD":55.37,"DiDeMo":32.37,"VATEX":29.88,"YouCook2":12.71,"QVHighlight":57.53,"Charades-STA":20.36,"MomentSeeker":41.22}
|
| 18 |
+
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-3B\">e5-omni-3B<\/a>","Model Size(B)":3.0,"Date":"2026-01-09","Video-Overall":40.63,"V-CLS":40.2,"V-QA":48.54,"V-RET":33.14,"V-MRET":40.67,"K700":41.9,"UCF101":58.0,"HMDB51":42.2,"SmthSmthV2":34.4,"Breakfast":24.48,"Video-MME":43.63,"MVBench":45.32,"NExTQA":54.37,"EgoSchema":36.6,"ActivityNetQA":62.8,"MSR-VTT":36.0,"MSVD":52.69,"DiDeMo":34.76,"VATEX":28.58,"YouCook2":13.68,"QVHighlight":62.6,"Charades-STA":18.16,"MomentSeeker":41.26}
|
| 19 |
+
{"Rank":19,"Models":"<a href=\"https:\/\/github.com\/GaryGuTC\/UniME-v2\">UniME-V2-LLaVA-OneVision-7B<\/a>","Model Size(B)":8.03,"Date":"2025-10-15","Video-Overall":39.01,"V-CLS":37.16,"V-QA":50.59,"V-RET":28.93,"V-MRET":39.59,"K700":38.0,"UCF101":61.8,"HMDB51":42.8,"SmthSmthV2":25.2,"Breakfast":18.01,"Video-MME":35.78,"MVBench":42.2,"NExTQA":58.76,"EgoSchema":51.6,"ActivityNetQA":64.6,"MSR-VTT":27.6,"MSVD":57.46,"DiDeMo":31.47,"VATEX":22.51,"YouCook2":5.6,"QVHighlight":56.79,"Charades-STA":29.99,"MomentSeeker":32.0}
|
| 20 |
+
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-7B-Instruct\">gme-Qwen2-VL-7B-Instruct<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Video-Overall":38.43,"V-CLS":37.27,"V-QA":50.28,"V-RET":28.26,"V-MRET":37.53,"K700":39.6,"UCF101":54.4,"HMDB51":48.0,"SmthSmthV2":30.5,"Breakfast":13.86,"Video-MME":39.19,"MVBench":46.3,"NExTQA":53.51,"EgoSchema":46.4,"ActivityNetQA":66.0,"MSR-VTT":31.8,"MSVD":49.55,"DiDeMo":26.29,"VATEX":24.74,"YouCook2":8.93,"QVHighlight":59.37,"Charades-STA":13.89,"MomentSeeker":39.33}
|
| 21 |
+
{"Rank":21,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-0.5B<\/a>","Model Size(B)":0.894,"Date":"2025-07-06","Video-Overall":35.87,"V-CLS":33.9,"V-QA":41.72,"V-RET":29.69,"V-MRET":39.69,"K700":33.6,"UCF101":47.2,"HMDB51":40.5,"SmthSmthV2":25.8,"Breakfast":22.4,"Video-MME":36.11,"MVBench":39.35,"NExTQA":38.36,"EgoSchema":26.2,"ActivityNetQA":68.6,"MSR-VTT":33.0,"MSVD":51.19,"DiDeMo":30.48,"VATEX":25.48,"YouCook2":8.3,"QVHighlight":56.14,"Charades-STA":23.11,"MomentSeeker":39.83}
|
| 22 |
+
{"Rank":22,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret\">LamRA-Ret<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Video-Overall":35.21,"V-CLS":39.41,"V-QA":42.74,"V-RET":24.47,"V-MRET":33.58,"K700":42.3,"UCF101":60.7,"HMDB51":40.4,"SmthSmthV2":36.1,"Breakfast":17.55,"Video-MME":34.07,"MVBench":37.33,"NExTQA":43.69,"EgoSchema":44.8,"ActivityNetQA":53.8,"MSR-VTT":22.6,"MSVD":46.42,"DiDeMo":25.0,"VATEX":19.09,"YouCook2":9.25,"QVHighlight":53.92,"Charades-STA":10.87,"MomentSeeker":35.96}
|
| 23 |
+
{"Rank":23,"Models":"<a href=\"https:\/\/huggingface.co\/VLM2Vec\/VLM2Vec-V2.0\">VLM2Vec-V2.0-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Video-Overall":34.67,"V-CLS":39.24,"V-QA":34.66,"V-RET":28.37,"V-MRET":37.55,"K700":38.2,"UCF101":60.0,"HMDB51":40.2,"SmthSmthV2":43.0,"Breakfast":14.78,"Video-MME":30.81,"MVBench":33.62,"NExTQA":20.88,"EgoSchema":35.0,"ActivityNetQA":53.0,"MSR-VTT":27.8,"MSVD":47.31,"DiDeMo":29.98,"VATEX":26.15,"YouCook2":10.63,"QVHighlight":49.68,"Charades-STA":20.08,"MomentSeeker":42.88}
|
| 24 |
+
{"Rank":24,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret-Qwen2.5VL-7b\">LamRA-Ret-Qwen2.5VL-7b<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Video-Overall":33.83,"V-CLS":32.61,"V-QA":42.7,"V-RET":23.68,"V-MRET":37.97,"K700":32.2,"UCF101":51.1,"HMDB51":34.4,"SmthSmthV2":25.5,"Breakfast":19.86,"Video-MME":35.33,"MVBench":37.5,"NExTQA":44.99,"EgoSchema":47.2,"ActivityNetQA":48.5,"MSR-VTT":25.9,"MSVD":42.84,"DiDeMo":23.71,"VATEX":18.29,"YouCook2":7.64,"QVHighlight":61.59,"Charades-STA":18.98,"MomentSeeker":33.33}
|
| 25 |
+
{"Rank":25,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-7B\">VLM2Vec-V1-Qwen2VL-7B<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Video-Overall":33.79,"V-CLS":38.99,"V-QA":30.09,"V-RET":29.08,"V-MRET":39.16,"K700":35.4,"UCF101":62.1,"HMDB51":41.9,"SmthSmthV2":32.0,"Breakfast":23.56,"Video-MME":28.04,"MVBench":28.55,"NExTQA":20.28,"EgoSchema":22.2,"ActivityNetQA":51.4,"MSR-VTT":34.7,"MSVD":46.72,"DiDeMo":29.58,"VATEX":25.37,"YouCook2":9.03,"QVHighlight":57.89,"Charades-STA":18.57,"MomentSeeker":41.01}
|
| 26 |
+
{"Rank":26,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-2B-Instruct\">gme-Qwen2-VL-2B-Instruct<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Video-Overall":33.59,"V-CLS":34.75,"V-QA":41.75,"V-RET":25.35,"V-MRET":31.8,"K700":34.9,"UCF101":52.1,"HMDB51":43.0,"SmthSmthV2":30.1,"Breakfast":13.63,"Video-MME":33.96,"MVBench":37.57,"NExTQA":39.4,"EgoSchema":40.6,"ActivityNetQA":57.2,"MSR-VTT":27.0,"MSVD":47.31,"DiDeMo":21.51,"VATEX":23.05,"YouCook2":7.9,"QVHighlight":43.95,"Charades-STA":14.31,"MomentSeeker":37.14}
|
| 27 |
+
{"Rank":27,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-2B\">VLM2Vec-V1-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Video-Overall":28.55,"V-CLS":33.27,"V-QA":30.66,"V-RET":20.45,"V-MRET":30.66,"K700":31.0,"UCF101":57.6,"HMDB51":34.0,"SmthSmthV2":30.8,"Breakfast":12.93,"Video-MME":27.07,"MVBench":30.53,"NExTQA":20.2,"EgoSchema":25.6,"ActivityNetQA":49.9,"MSR-VTT":25.6,"MSVD":37.46,"DiDeMo":19.12,"VATEX":15.68,"YouCook2":4.37,"QVHighlight":43.67,"Charades-STA":12.93,"MomentSeeker":35.39}
|
| 28 |
+
{"Rank":28,"Models":"colpali-v1.3","Model Size(B)":"unknown","Date":"2025-12-29","Video-Overall":28.23,"V-CLS":26.63,"V-QA":37.82,"V-RET":21.48,"V-MRET":26.16,"K700":23.3,"UCF101":49.3,"HMDB51":24.8,"SmthSmthV2":24.9,"Breakfast":10.85,"Video-MME":30.59,"MVBench":33.58,"NExTQA":35.15,"EgoSchema":38.4,"ActivityNetQA":51.4,"MSR-VTT":17.7,"MSVD":45.37,"DiDeMo":22.51,"VATEX":16.68,"YouCook2":5.16,"QVHighlight":20.13,"Charades-STA":29.02,"MomentSeeker":29.34}
|
| 29 |
+
{"Rank":29,"Models":"QQMM-embed-v3","Model Size(B)":8.29,"Date":"2025-12-30","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 30 |
+
{"Rank":30,"Models":"<a href=\"https:\/\/github.com\/QQ-MM\/QQMM-embed\">QQMM-embed-v2<\/a>","Model Size(B)":8.29,"Date":"2025-09-15","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 31 |
+
{"Rank":31,"Models":"UniVec-CoT-7B","Model Size(B)":8.29,"Date":"unknown","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 32 |
+
{"Rank":32,"Models":"OEmbedding-v1-7B","Model Size(B)":8.29,"Date":"2025-10-14","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 33 |
+
{"Rank":33,"Models":"ReCo-7B","Model Size(B)":8.29,"Date":"2025-08-15","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 34 |
+
{"Rank":34,"Models":"UniVec-7B","Model Size(B)":8.29,"Date":"unknown","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 35 |
+
{"Rank":35,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-7B<\/a>","Model Size(B)":8.29,"Date":"2025-11-24","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 36 |
+
{"Rank":36,"Models":"dp-embedding-v3-lite","Model Size(B)":8.29,"Date":"2025-12-15","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 37 |
+
{"Rank":37,"Models":"TCE-v1","Model Size(B)":8.0,"Date":"2025-10-31","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 38 |
+
{"Rank":38,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-3B<\/a>","Model Size(B)":3.75,"Date":"2025-11-24","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 39 |
+
{"Rank":39,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-2B<\/a>","Model Size(B)":2.21,"Date":"2025-11-24","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 40 |
+
{"Rank":40,"Models":"Taichu-UniRetriever-8B","Model Size(B)":8.77,"Date":"2026-01-15","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 41 |
+
{"Rank":41,"Models":"Taichu-UniRetriever-v1-2B","Model Size(B)":2.13,"Date":"2026-01-06","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
| 42 |
+
{"Rank":42,"Models":"TCR","Model Size(B)":8.77,"Date":"2026-01-15","Video-Overall":0.0,"V-CLS":0.0,"V-QA":0.0,"V-RET":0.0,"V-MRET":0.0,"K700":0.0,"UCF101":0.0,"HMDB51":0.0,"SmthSmthV2":0.0,"Breakfast":0.0,"Video-MME":0.0,"MVBench":0.0,"NExTQA":0.0,"EgoSchema":0.0,"ActivityNetQA":0.0,"MSR-VTT":0.0,"MSVD":0.0,"DiDeMo":0.0,"VATEX":0.0,"YouCook2":0.0,"QVHighlight":0.0,"Charades-STA":0.0,"MomentSeeker":0.0}
|
rankings/visdoc_ranking.csv
CHANGED
|
@@ -1,25 +1,43 @@
|
|
| 1 |
-
Rank,Models,Model Size(B),Visdoc-Overall,ViDoRe-V1,ViDoRe-V2,VisRAG,VisDoc-OOD,ViDoRe_arxivqa,ViDoRe_docvqa,ViDoRe_infovqa,ViDoRe_tabfquad,ViDoRe_tatdqa,ViDoRe_shiftproject,ViDoRe_syntheticDocQA_artificial_intelligence,ViDoRe_syntheticDocQA_energy,ViDoRe_syntheticDocQA_government_reports,ViDoRe_syntheticDocQA_healthcare_industry,ViDoRe_esg_reports_human_labeled_v2,ViDoRe_biomedical_lectures_v2_multilingual,ViDoRe_economics_reports_v2_multilingual,ViDoRe_esg_reports_v2_multilingual,VisRAG_ArxivQA,VisRAG_ChartQA,VisRAG_MP-DocVQA,VisRAG_SlideVQA,VisRAG_InfoVQA,VisRAG_PlotQA,ViDoSeek-
|
| 2 |
-
1,
|
| 3 |
-
2,"<a href=""https://
|
| 4 |
-
3,
|
| 5 |
-
4,"<a href=""https://huggingface.co/
|
| 6 |
-
5,
|
| 7 |
-
6,"<a href=""https://
|
| 8 |
-
7,
|
| 9 |
-
8,
|
| 10 |
-
9,"<a href=""https://huggingface.co/
|
| 11 |
-
10,"<a href=""https://huggingface.co/
|
| 12 |
-
11,
|
| 13 |
-
12,
|
| 14 |
-
13,"<a href=""https://
|
| 15 |
-
14,"<a href=""https://huggingface.co/
|
| 16 |
-
15,"<a href=""https://
|
| 17 |
-
16,"<a href=""https://
|
| 18 |
-
17,
|
| 19 |
-
18,"<a href=""https://huggingface.co/
|
| 20 |
-
19,"<a href=""https://huggingface.co/
|
| 21 |
-
20,"<a href=""https://huggingface.co/
|
| 22 |
-
21,
|
| 23 |
-
22,
|
| 24 |
-
23,
|
| 25 |
-
24,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Rank,Models,Model Size(B),Date,Visdoc-Overall,ViDoRe-V1,ViDoRe-V2,VisRAG,VisDoc-OOD,ViDoRe_arxivqa,ViDoRe_docvqa,ViDoRe_infovqa,ViDoRe_tabfquad,ViDoRe_tatdqa,ViDoRe_shiftproject,ViDoRe_syntheticDocQA_artificial_intelligence,ViDoRe_syntheticDocQA_energy,ViDoRe_syntheticDocQA_government_reports,ViDoRe_syntheticDocQA_healthcare_industry,ViDoRe_esg_reports_human_labeled_v2,ViDoRe_biomedical_lectures_v2_multilingual,ViDoRe_economics_reports_v2_multilingual,ViDoRe_esg_reports_v2_multilingual,VisRAG_ArxivQA,VisRAG_ChartQA,VisRAG_MP-DocVQA,VisRAG_SlideVQA,VisRAG_InfoVQA,VisRAG_PlotQA,ViDoSeek-doc,MMLongBench-doc,ViDoSeek-page-fixed,MMLongBench-page-fixed,ViDoSeek-page-old,MMLongBench-page-old
|
| 2 |
+
1,Taichu-UniRetriever-8B,8.77,2026-01-15,83.72,90.93,62.91,89.66,71.45,90.06,61.9,93.93,97.33,80.53,93.2,98.89,97.5,97.05,98.89,69.67,65.62,55.32,61.02,88.58,90.2,91.47,97.39,97.03,73.3,85.62,57.28,92.42,63.78,✅,✅
|
| 3 |
+
2,"<a href=""https://console.volcengine.com/ark/region:ark+cn-beijing/model/detail?Id=doubao-embedding-vision"">seed1.6-embedding-1215</a>",unknown,2025-12-18,83.16,90.9,60.31,89.96,69.82,92.29,61.84,94.28,94.99,80.41,91.71,99.26,96.76,98.15,99.26,70.52,63.46,55.44,51.82,90.49,87.59,94.07,97.3,95.87,74.47,84.27,55.37,⚠️! Please fix this score!,⚠️! Please fix this score!,22.29,17.15
|
| 4 |
+
3,"<a href=""https://interestfm-tte.github.io/"">IFM-TTE-7B</a>",8.29,2025-10-11,83.14,85.19,71.5,92.75,67.31,84.53,45.76,88.33,94.28,55.31,89.76,99.26,97.26,98.28,99.13,87.5,64.85,53.94,79.73,92.73,95.07,87.31,95.9,93.0,92.49,82.6,52.03,⚠️! Please fix this score!,⚠️! Please fix this score!,50.29,28.18
|
| 5 |
+
4,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B"">Qwen3-VL-Embedding-8B</a>",8.14,2026-01-06,83.09,87.21,69.86,88.68,72.19,87.0,54.02,90.86,96.67,69.97,84.14,99.26,94.41,98.02,97.79,71.39,71.59,67.18,69.28,88.21,88.34,89.27,96.73,94.75,74.8,86.1,58.29,88.38,60.29,✅,✅
|
| 6 |
+
5,WeMM-Embedding-8B,8.77,2025-12-16,82.49,89.47,59.31,90.43,70.13,92.22,60.95,92.83,93.41,77.03,88.5,98.15,96.21,96.17,99.26,62.97,61.9,56.85,55.51,90.42,91.4,91.82,97.0,95.97,75.95,84.31,55.95,⚠️! Please fix this score!,⚠️! Please fix this score!,23.34,17.05
|
| 7 |
+
6,"<a href=""https://github.com/360CVGroup/RzenEmbed"">RzenEmbed-v2-7B</a>",8.29,2025-09-20,82.31,89.7,60.7,88.7,69.4,88.42,59.61,92.85,95.85,76.5,91.76,99.63,95.71,97.02,99.63,65.61,61.71,59.1,56.39,89.38,89.61,90.59,95.68,94.11,72.81,84.02,54.78,⚠️! Please fix this score!,⚠️! Please fix this score!,23.09,15.62
|
| 8 |
+
7,RzenEmbed-v1-7B,8.29,2025-07-30,82.0,89.47,60.77,87.92,69.3,86.89,57.99,92.24,96.25,75.22,93.35,99.63,95.25,98.28,99.63,63.67,61.58,60.8,57.05,86.97,88.34,90.7,95.75,94.37,71.39,83.92,54.67,⚠️! Please fix this score!,⚠️! Please fix this score!,23.06,16.1
|
| 9 |
+
8,Taichu-UniRetriever-v1-2B,2.13,2026-01-06,81.93,89.81,57.34,88.79,71.13,88.14,59.09,92.63,96.67,80.07,89.93,99.26,98.06,95.93,98.32,63.6,62.47,51.21,52.08,87.25,87.33,91.99,96.93,95.9,73.32,85.07,57.19,⚠️! Please fix this score!,⚠️! Please fix this score!,20.92,16.49
|
| 10 |
+
9,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-7B"">e5-omni-7B</a>",8.0,2026-01-09,81.3,87.58,62.39,87.46,69.21,87.57,57.96,92.29,93.19,70.9,85.79,98.15,94.95,96.28,98.69,64.03,64.48,60.34,60.71,88.02,89.02,89.07,95.99,93.54,69.15,83.44,54.98,⚠️! Please fix this score!,⚠️! Please fix this score!,23.11,15.78
|
| 11 |
+
10,"<a href=""https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B"">Qwen3-VL-Embedding-2B</a>",2.13,2026-01-06,80.16,84.37,65.34,86.43,70.0,81.8,49.36,88.35,96.4,63.19,83.9,97.05,90.84,95.68,97.09,64.56,68.23,63.09,65.49,83.58,87.13,87.06,95.59,92.88,72.33,85.0,54.99,81.94,55.73,✅,✅
|
| 12 |
+
11,WeMM-Embedding-2B,2.13,2025-12-16,79.85,87.22,53.4,88.84,68.89,90.25,59.11,91.2,89.41,73.81,82.61,98.15,94.08,95.35,98.28,54.54,55.64,53.93,49.5,88.62,88.61,91.01,95.83,93.74,75.23,83.14,54.65,⚠️! Please fix this score!,⚠️! Please fix this score!,22.27,16.53
|
| 13 |
+
12,RzenEmbed-v1-2B,2.21,2025-07-16,79.4,86.98,57.63,85.35,67.11,83.4,56.09,89.89,94.39,69.32,89.88,98.76,92.78,97.19,98.15,58.93,59.87,57.98,53.73,83.68,86.39,85.54,94.07,91.92,70.52,82.27,51.95,⚠️! Please fix this score!,⚠️! Please fix this score!,22.89,16.21
|
| 14 |
+
13,"<a href=""https://seed1-6-embedding.github.io"">seed-1.6-embedding</a>",unknown,2025-06-17,78.37,85.53,56.57,84.74,67.09,88.46,60.36,90.62,87.82,74.98,73.34,96.32,92.83,93.54,97.05,63.3,57.14,53.85,51.99,85.79,81.88,89.43,94.9,92.41,64.02,82.57,51.61,⚠️! Please fix this score!,⚠️! Please fix this score!,22.8,15.57
|
| 15 |
+
14,"<a href=""https://huggingface.co/Haon-Chen/e5-omni-3B"">e5-omni-3B</a>",3.0,2026-01-09,78.11,83.13,59.53,85.48,68.07,82.2,51.99,88.88,88.86,58.78,80.14,98.15,93.17,93.21,95.92,61.84,60.92,64.39,50.97,84.52,86.75,85.51,95.4,92.55,68.17,83.29,52.85,⚠️! Please fix this score!,⚠️! Please fix this score!,22.38,15.0
|
| 16 |
+
15,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-7B"">Ops-MM-embedding-v1-7B</a>",8.29,2025-07-02,74.99,80.05,59.59,79.31,67.49,78.17,49.11,86.59,91.4,55.59,76.17,90.99,87.53,91.56,93.39,66.27,54.34,60.92,56.82,78.18,79.53,78.2,91.11,87.16,61.71,83.47,51.51,⚠️! Please fix this score!,⚠️! Please fix this score!,22.47,15.89
|
| 17 |
+
16,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-7B-Instruct"">gme-Qwen2-VL-7B-Instruct</a>",8.29,2025-12-29,73.96,89.55,55.47,84.95,0.0,87.53,56.59,92.17,92.71,76.58,95.64,99.63,95.69,99.5,99.5,62.76,49.78,53.91,55.43,87.69,81.29,89.08,94.72,93.49,63.44,0.0,0.0,83.57,55.32,✅,✅
|
| 18 |
+
17,Crotchet-embedding-2B,2.13,2025-12-31,73.59,78.16,53.28,82.21,65.51,84.34,42.93,85.18,93.29,53.04,71.02,90.74,85.07,85.45,90.59,62.65,46.92,51.47,52.09,81.64,85.47,76.0,90.85,88.54,70.74,81.84,49.18,⚠️! Please fix this score!,⚠️! Please fix this score!,78.36,51.39
|
| 19 |
+
18,"<a href=""https://huggingface.co/Alibaba-NLP/gme-Qwen2-VL-2B-Instruct"">gme-Qwen2-VL-2B-Instruct</a>",2.21,2025-12-29,71.88,87.12,53.88,82.43,0.0,82.53,55.16,90.69,93.31,70.26,92.85,98.13,92.56,97.15,98.52,60.29,53.99,50.8,50.43,81.95,79.09,84.34,93.68,91.41,64.12,0.0,0.0,79.81,51.32,✅,✅
|
| 20 |
+
19,"<a href=""https://huggingface.co/zhibinlan/UME-R1-7B"">UME-R1-7B</a>",8.29,2025-10-20,71.71,75.66,50.53,83.7,58.3,73.56,41.1,80.83,90.24,46.67,64.96,89.47,85.7,89.82,94.29,50.41,50.73,57.8,43.18,80.45,84.95,83.43,91.47,89.2,72.7,75.33,41.28,⚠️! Please fix this score!,⚠️! Please fix this score!,21.28,12.32
|
| 21 |
+
20,"<a href=""https://huggingface.co/OpenSearch-AI/Ops-MM-embedding-v1-2B"">Ops-MM-embedding-v1-2B</a>",2.21,2025-07-02,71.48,76.39,53.18,77.64,65.09,73.72,45.01,81.41,88.81,49.59,72.57,89.8,84.27,87.06,91.64,58.57,52.87,47.89,53.39,73.84,80.17,75.06,89.15,86.66,60.99,82.29,47.89,⚠️! Please fix this score!,⚠️! Please fix this score!,21.44,13.06
|
| 22 |
+
21,colpali-v1.3,unknown,2025-12-29,70.5,84.57,54.81,81.0,0.0,83.33,59.2,85.38,86.63,70.47,76.83,96.26,95.02,95.59,97.02,57.25,56.25,50.2,55.56,80.9,77.04,87.03,95.13,85.73,60.18,0.0,0.0,79.22,53.18,✅,✅
|
| 23 |
+
22,"<a href=""https://huggingface.co/zhibinlan/UME-R1-2B"">UME-R1-2B</a>",2.21,2025-10-20,68.16,72.39,46.16,79.22,57.78,73.86,37.85,76.19,86.11,40.63,66.79,85.87,83.25,82.56,90.83,50.16,46.15,45.69,42.65,74.26,85.98,75.59,87.11,84.38,67.98,75.89,39.68,⚠️! Please fix this score!,⚠️! Please fix this score!,21.2,11.9
|
| 24 |
+
23,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-7B</a>",8.03,2025-07-06,68.1,70.68,49.57,79.45,58.21,73.29,38.27,80.59,80.7,37.79,52.02,85.99,84.78,84.96,88.37,50.67,50.89,54.38,42.33,73.96,82.71,75.15,87.58,87.91,69.42,73.82,42.61,⚠️! Please fix this score!,⚠️! Please fix this score!,22.52,13.32
|
| 25 |
+
24,"<a href=""https://huggingface.co/VLM2Vec/VLM2Vec-V2.0"">VLM2Vec-V2.0-Qwen2VL-2B</a>",2.21,2025-12-29,63.56,74.39,44.61,79.33,0.0,78.87,37.06,82.71,87.77,44.29,61.04,89.12,86.29,85.58,91.13,45.79,44.59,42.33,45.74,76.74,84.2,71.8,91.44,85.88,65.91,0.0,0.0,80.3,44.7,✅,✅
|
| 26 |
+
25,"<a href=""https://github.com/GaryGuTC/UniME-v2"">UniME-V2-LLaVA-OneVision-7B</a>",8.03,2025-10-15,60.24,61.76,42.0,70.53,58.3,51.9,38.17,73.16,57.75,35.48,45.42,76.85,77.27,79.87,81.71,54.67,33.75,35.95,43.63,53.13,83.67,66.4,86.44,82.58,50.96,75.79,40.8,⚠️! Please fix this score!,⚠️! Please fix this score!,22.89,11.96
|
| 27 |
+
26,"<a href=""https://arxiv.org/abs/2503.19900"">interestFM-UIR-CAFe-0.5B</a>",0.894,2025-07-06,54.83,56.93,32.59,68.57,47.59,51.19,25.46,71.95,59.64,27.05,31.8,78.74,70.75,75.47,77.29,36.24,29.72,37.61,26.78,57.82,75.62,63.24,82.32,80.28,52.14,61.41,33.78,⚠️! Please fix this score!,⚠️! Please fix this score!,17.62,9.95
|
| 28 |
+
27,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret-Qwen2.5VL-7b"">LamRA-Ret-Qwen2.5VL-7b</a>",8.29,2025-12-29,47.61,56.4,33.62,58.15,0.0,53.04,25.42,72.19,66.51,26.01,28.13,70.31,66.33,72.21,83.8,32.98,35.87,32.37,33.26,38.03,65.21,54.14,76.55,73.5,41.46,0.0,0.0,68.54,35.83,✅,✅
|
| 29 |
+
28,"<a href=""https://huggingface.co/code-kunkun/LamRA-Ret"">LamRA-Ret</a>",8.29,2025-12-29,27.72,33.83,11.53,37.56,0.0,31.54,19.85,63.67,53.47,7.88,15.95,29.83,36.05,41.18,38.83,6.91,13.42,19.37,6.43,2.04,42.74,33.37,56.3,56.86,34.06,0.0,0.0,34.48,18.29,✅,✅
|
| 30 |
+
29,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-7B"">VLM2Vec-V1-Qwen2VL-7B</a>",8.29,2025-12-29,26.82,19.99,9.24,58.85,0.0,28.16,18.98,44.77,16.98,5.73,1.63,18.23,23.9,13.88,27.61,6.95,5.22,13.75,11.05,52.85,68.96,52.74,72.76,71.3,34.52,0.0,0.0,77.4,36.76,✅,✅
|
| 31 |
+
30,"<a href=""https://huggingface.co/TIGER-Lab/VLM2Vec-Qwen2VL-2B"">VLM2Vec-V1-Qwen2VL-2B</a>",2.21,2025-12-29,26.0,20.59,13.19,52.23,0.0,18.12,14.01,39.53,36.03,10.49,8.41,17.04,16.35,25.15,20.79,13.05,6.51,12.86,20.32,41.22,59.48,43.55,74.5,71.1,23.51,0.0,0.0,67.81,26.04,✅,✅
|
| 32 |
+
31,dp-embedding-v3-lite,8.29,2025-12-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 33 |
+
32,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-2B</a>",2.21,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 34 |
+
33,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-3B</a>",3.75,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 35 |
+
34,TCE-v1,8.0,2025-10-31,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 36 |
+
35,UniVec-CoT-7B,8.29,unknown,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 37 |
+
36,"<a href=""https://arxiv.org/abs/2511.19278"">ReMatch-7B</a>",8.29,2025-11-24,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 38 |
+
37,UniVec-7B,8.29,unknown,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 39 |
+
38,ReCo-7B,8.29,2025-08-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 40 |
+
39,OEmbedding-v1-7B,8.29,2025-10-14,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 41 |
+
40,"<a href=""https://github.com/QQ-MM/QQMM-embed"">QQMM-embed-v2</a>",8.29,2025-09-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 42 |
+
41,QQMM-embed-v3,8.29,2025-12-30,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
| 43 |
+
42,TCR,8.77,2026-01-15,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,✅,✅
|
rankings/visdoc_ranking.jsonl
CHANGED
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{"Rank":1,"Models":"
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{"Rank":2,"Models":"<a href=\"https:\/\/
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{"Rank":3,"Models":"
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{"Rank":4,"Models":"<a href=\"https:\/\/huggingface.co\/
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{"Rank":5,"Models":"
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{"Rank":6,"Models":"<a href=\"https:\/\/
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{"Rank":7,"Models":"
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{"Rank":8,"Models":"
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{"Rank":9,"Models":"<a href=\"https:\/\/huggingface.co\/
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{"Rank":10,"Models":"<a href=\"https:\/\/huggingface.co\/
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{"Rank":11,"Models":"
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{"Rank":12,"Models":"
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{"Rank":13,"Models":"<a href=\"https:\/\/
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-
{"Rank":14,"Models":"<a href=\"https:\/\/huggingface.co\/
|
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-
{"Rank":15,"Models":"<a href=\"https:\/\/
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-
{"Rank":16,"Models":"<a href=\"https:\/\/
|
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-
{"Rank":17,"Models":"
|
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-
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/
|
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-
{"Rank":19,"Models":"<a href=\"https:\/\/huggingface.co\/
|
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-
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/
|
| 21 |
-
{"Rank":21,"Models":"
|
| 22 |
-
{"Rank":22,"Models":"
|
| 23 |
-
{"Rank":23,"Models":"
|
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-
{"Rank":24,"Models":"
|
|
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| 1 |
+
{"Rank":1,"Models":"Taichu-UniRetriever-8B","Model Size(B)":8.77,"Date":"2026-01-15","Visdoc-Overall":83.72,"ViDoRe-V1":90.93,"ViDoRe-V2":62.91,"VisRAG":89.66,"VisDoc-OOD":71.45,"ViDoRe_arxivqa":90.06,"ViDoRe_docvqa":61.9,"ViDoRe_infovqa":93.93,"ViDoRe_tabfquad":97.33,"ViDoRe_tatdqa":80.53,"ViDoRe_shiftproject":93.2,"ViDoRe_syntheticDocQA_artificial_intelligence":98.89,"ViDoRe_syntheticDocQA_energy":97.5,"ViDoRe_syntheticDocQA_government_reports":97.05,"ViDoRe_syntheticDocQA_healthcare_industry":98.89,"ViDoRe_esg_reports_human_labeled_v2":69.67,"ViDoRe_biomedical_lectures_v2_multilingual":65.62,"ViDoRe_economics_reports_v2_multilingual":55.32,"ViDoRe_esg_reports_v2_multilingual":61.02,"VisRAG_ArxivQA":88.58,"VisRAG_ChartQA":90.2,"VisRAG_MP-DocVQA":91.47,"VisRAG_SlideVQA":97.39,"VisRAG_InfoVQA":97.03,"VisRAG_PlotQA":73.3,"ViDoSeek-doc":85.62,"MMLongBench-doc":57.28,"ViDoSeek-page-fixed":92.42,"MMLongBench-page-fixed":63.78,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 2 |
+
{"Rank":2,"Models":"<a href=\"https:\/\/console.volcengine.com\/ark\/region:ark+cn-beijing\/model\/detail?Id=doubao-embedding-vision\">seed1.6-embedding-1215<\/a>","Model Size(B)":"unknown","Date":"2025-12-18","Visdoc-Overall":83.16,"ViDoRe-V1":90.9,"ViDoRe-V2":60.31,"VisRAG":89.96,"VisDoc-OOD":69.82,"ViDoRe_arxivqa":92.29,"ViDoRe_docvqa":61.84,"ViDoRe_infovqa":94.28,"ViDoRe_tabfquad":94.99,"ViDoRe_tatdqa":80.41,"ViDoRe_shiftproject":91.71,"ViDoRe_syntheticDocQA_artificial_intelligence":99.26,"ViDoRe_syntheticDocQA_energy":96.76,"ViDoRe_syntheticDocQA_government_reports":98.15,"ViDoRe_syntheticDocQA_healthcare_industry":99.26,"ViDoRe_esg_reports_human_labeled_v2":70.52,"ViDoRe_biomedical_lectures_v2_multilingual":63.46,"ViDoRe_economics_reports_v2_multilingual":55.44,"ViDoRe_esg_reports_v2_multilingual":51.82,"VisRAG_ArxivQA":90.49,"VisRAG_ChartQA":87.59,"VisRAG_MP-DocVQA":94.07,"VisRAG_SlideVQA":97.3,"VisRAG_InfoVQA":95.87,"VisRAG_PlotQA":74.47,"ViDoSeek-doc":84.27,"MMLongBench-doc":55.37,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.29,"MMLongBench-page-old":17.15}
|
| 3 |
+
{"Rank":3,"Models":"<a href=\"https:\/\/interestfm-tte.github.io\/\">IFM-TTE-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-11","Visdoc-Overall":83.14,"ViDoRe-V1":85.19,"ViDoRe-V2":71.5,"VisRAG":92.75,"VisDoc-OOD":67.31,"ViDoRe_arxivqa":84.53,"ViDoRe_docvqa":45.76,"ViDoRe_infovqa":88.33,"ViDoRe_tabfquad":94.28,"ViDoRe_tatdqa":55.31,"ViDoRe_shiftproject":89.76,"ViDoRe_syntheticDocQA_artificial_intelligence":99.26,"ViDoRe_syntheticDocQA_energy":97.26,"ViDoRe_syntheticDocQA_government_reports":98.28,"ViDoRe_syntheticDocQA_healthcare_industry":99.13,"ViDoRe_esg_reports_human_labeled_v2":87.5,"ViDoRe_biomedical_lectures_v2_multilingual":64.85,"ViDoRe_economics_reports_v2_multilingual":53.94,"ViDoRe_esg_reports_v2_multilingual":79.73,"VisRAG_ArxivQA":92.73,"VisRAG_ChartQA":95.07,"VisRAG_MP-DocVQA":87.31,"VisRAG_SlideVQA":95.9,"VisRAG_InfoVQA":93.0,"VisRAG_PlotQA":92.49,"ViDoSeek-doc":82.6,"MMLongBench-doc":52.03,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":50.29,"MMLongBench-page-old":28.18}
|
| 4 |
+
{"Rank":4,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-8B\">Qwen3-VL-Embedding-8B<\/a>","Model Size(B)":8.14,"Date":"2026-01-06","Visdoc-Overall":83.09,"ViDoRe-V1":87.21,"ViDoRe-V2":69.86,"VisRAG":88.68,"VisDoc-OOD":72.19,"ViDoRe_arxivqa":87.0,"ViDoRe_docvqa":54.02,"ViDoRe_infovqa":90.86,"ViDoRe_tabfquad":96.67,"ViDoRe_tatdqa":69.97,"ViDoRe_shiftproject":84.14,"ViDoRe_syntheticDocQA_artificial_intelligence":99.26,"ViDoRe_syntheticDocQA_energy":94.41,"ViDoRe_syntheticDocQA_government_reports":98.02,"ViDoRe_syntheticDocQA_healthcare_industry":97.79,"ViDoRe_esg_reports_human_labeled_v2":71.39,"ViDoRe_biomedical_lectures_v2_multilingual":71.59,"ViDoRe_economics_reports_v2_multilingual":67.18,"ViDoRe_esg_reports_v2_multilingual":69.28,"VisRAG_ArxivQA":88.21,"VisRAG_ChartQA":88.34,"VisRAG_MP-DocVQA":89.27,"VisRAG_SlideVQA":96.73,"VisRAG_InfoVQA":94.75,"VisRAG_PlotQA":74.8,"ViDoSeek-doc":86.1,"MMLongBench-doc":58.29,"ViDoSeek-page-fixed":88.38,"MMLongBench-page-fixed":60.29,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 5 |
+
{"Rank":5,"Models":"WeMM-Embedding-8B","Model Size(B)":8.77,"Date":"2025-12-16","Visdoc-Overall":82.49,"ViDoRe-V1":89.47,"ViDoRe-V2":59.31,"VisRAG":90.43,"VisDoc-OOD":70.13,"ViDoRe_arxivqa":92.22,"ViDoRe_docvqa":60.95,"ViDoRe_infovqa":92.83,"ViDoRe_tabfquad":93.41,"ViDoRe_tatdqa":77.03,"ViDoRe_shiftproject":88.5,"ViDoRe_syntheticDocQA_artificial_intelligence":98.15,"ViDoRe_syntheticDocQA_energy":96.21,"ViDoRe_syntheticDocQA_government_reports":96.17,"ViDoRe_syntheticDocQA_healthcare_industry":99.26,"ViDoRe_esg_reports_human_labeled_v2":62.97,"ViDoRe_biomedical_lectures_v2_multilingual":61.9,"ViDoRe_economics_reports_v2_multilingual":56.85,"ViDoRe_esg_reports_v2_multilingual":55.51,"VisRAG_ArxivQA":90.42,"VisRAG_ChartQA":91.4,"VisRAG_MP-DocVQA":91.82,"VisRAG_SlideVQA":97.0,"VisRAG_InfoVQA":95.97,"VisRAG_PlotQA":75.95,"ViDoSeek-doc":84.31,"MMLongBench-doc":55.95,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":23.34,"MMLongBench-page-old":17.05}
|
| 6 |
+
{"Rank":6,"Models":"<a href=\"https:\/\/github.com\/360CVGroup\/RzenEmbed\">RzenEmbed-v2-7B<\/a>","Model Size(B)":8.29,"Date":"2025-09-20","Visdoc-Overall":82.31,"ViDoRe-V1":89.7,"ViDoRe-V2":60.7,"VisRAG":88.7,"VisDoc-OOD":69.4,"ViDoRe_arxivqa":88.42,"ViDoRe_docvqa":59.61,"ViDoRe_infovqa":92.85,"ViDoRe_tabfquad":95.85,"ViDoRe_tatdqa":76.5,"ViDoRe_shiftproject":91.76,"ViDoRe_syntheticDocQA_artificial_intelligence":99.63,"ViDoRe_syntheticDocQA_energy":95.71,"ViDoRe_syntheticDocQA_government_reports":97.02,"ViDoRe_syntheticDocQA_healthcare_industry":99.63,"ViDoRe_esg_reports_human_labeled_v2":65.61,"ViDoRe_biomedical_lectures_v2_multilingual":61.71,"ViDoRe_economics_reports_v2_multilingual":59.1,"ViDoRe_esg_reports_v2_multilingual":56.39,"VisRAG_ArxivQA":89.38,"VisRAG_ChartQA":89.61,"VisRAG_MP-DocVQA":90.59,"VisRAG_SlideVQA":95.68,"VisRAG_InfoVQA":94.11,"VisRAG_PlotQA":72.81,"ViDoSeek-doc":84.02,"MMLongBench-doc":54.78,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":23.09,"MMLongBench-page-old":15.62}
|
| 7 |
+
{"Rank":7,"Models":"RzenEmbed-v1-7B","Model Size(B)":8.29,"Date":"2025-07-30","Visdoc-Overall":82.0,"ViDoRe-V1":89.47,"ViDoRe-V2":60.77,"VisRAG":87.92,"VisDoc-OOD":69.3,"ViDoRe_arxivqa":86.89,"ViDoRe_docvqa":57.99,"ViDoRe_infovqa":92.24,"ViDoRe_tabfquad":96.25,"ViDoRe_tatdqa":75.22,"ViDoRe_shiftproject":93.35,"ViDoRe_syntheticDocQA_artificial_intelligence":99.63,"ViDoRe_syntheticDocQA_energy":95.25,"ViDoRe_syntheticDocQA_government_reports":98.28,"ViDoRe_syntheticDocQA_healthcare_industry":99.63,"ViDoRe_esg_reports_human_labeled_v2":63.67,"ViDoRe_biomedical_lectures_v2_multilingual":61.58,"ViDoRe_economics_reports_v2_multilingual":60.8,"ViDoRe_esg_reports_v2_multilingual":57.05,"VisRAG_ArxivQA":86.97,"VisRAG_ChartQA":88.34,"VisRAG_MP-DocVQA":90.7,"VisRAG_SlideVQA":95.75,"VisRAG_InfoVQA":94.37,"VisRAG_PlotQA":71.39,"ViDoSeek-doc":83.92,"MMLongBench-doc":54.67,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":23.06,"MMLongBench-page-old":16.1}
|
| 8 |
+
{"Rank":8,"Models":"Taichu-UniRetriever-v1-2B","Model Size(B)":2.13,"Date":"2026-01-06","Visdoc-Overall":81.93,"ViDoRe-V1":89.81,"ViDoRe-V2":57.34,"VisRAG":88.79,"VisDoc-OOD":71.13,"ViDoRe_arxivqa":88.14,"ViDoRe_docvqa":59.09,"ViDoRe_infovqa":92.63,"ViDoRe_tabfquad":96.67,"ViDoRe_tatdqa":80.07,"ViDoRe_shiftproject":89.93,"ViDoRe_syntheticDocQA_artificial_intelligence":99.26,"ViDoRe_syntheticDocQA_energy":98.06,"ViDoRe_syntheticDocQA_government_reports":95.93,"ViDoRe_syntheticDocQA_healthcare_industry":98.32,"ViDoRe_esg_reports_human_labeled_v2":63.6,"ViDoRe_biomedical_lectures_v2_multilingual":62.47,"ViDoRe_economics_reports_v2_multilingual":51.21,"ViDoRe_esg_reports_v2_multilingual":52.08,"VisRAG_ArxivQA":87.25,"VisRAG_ChartQA":87.33,"VisRAG_MP-DocVQA":91.99,"VisRAG_SlideVQA":96.93,"VisRAG_InfoVQA":95.9,"VisRAG_PlotQA":73.32,"ViDoSeek-doc":85.07,"MMLongBench-doc":57.19,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":20.92,"MMLongBench-page-old":16.49}
|
| 9 |
+
{"Rank":9,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-7B\">e5-omni-7B<\/a>","Model Size(B)":8.0,"Date":"2026-01-09","Visdoc-Overall":81.3,"ViDoRe-V1":87.58,"ViDoRe-V2":62.39,"VisRAG":87.46,"VisDoc-OOD":69.21,"ViDoRe_arxivqa":87.57,"ViDoRe_docvqa":57.96,"ViDoRe_infovqa":92.29,"ViDoRe_tabfquad":93.19,"ViDoRe_tatdqa":70.9,"ViDoRe_shiftproject":85.79,"ViDoRe_syntheticDocQA_artificial_intelligence":98.15,"ViDoRe_syntheticDocQA_energy":94.95,"ViDoRe_syntheticDocQA_government_reports":96.28,"ViDoRe_syntheticDocQA_healthcare_industry":98.69,"ViDoRe_esg_reports_human_labeled_v2":64.03,"ViDoRe_biomedical_lectures_v2_multilingual":64.48,"ViDoRe_economics_reports_v2_multilingual":60.34,"ViDoRe_esg_reports_v2_multilingual":60.71,"VisRAG_ArxivQA":88.02,"VisRAG_ChartQA":89.02,"VisRAG_MP-DocVQA":89.07,"VisRAG_SlideVQA":95.99,"VisRAG_InfoVQA":93.54,"VisRAG_PlotQA":69.15,"ViDoSeek-doc":83.44,"MMLongBench-doc":54.98,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":23.11,"MMLongBench-page-old":15.78}
|
| 10 |
+
{"Rank":10,"Models":"<a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-VL-Embedding-2B\">Qwen3-VL-Embedding-2B<\/a>","Model Size(B)":2.13,"Date":"2026-01-06","Visdoc-Overall":80.16,"ViDoRe-V1":84.37,"ViDoRe-V2":65.34,"VisRAG":86.43,"VisDoc-OOD":70.0,"ViDoRe_arxivqa":81.8,"ViDoRe_docvqa":49.36,"ViDoRe_infovqa":88.35,"ViDoRe_tabfquad":96.4,"ViDoRe_tatdqa":63.19,"ViDoRe_shiftproject":83.9,"ViDoRe_syntheticDocQA_artificial_intelligence":97.05,"ViDoRe_syntheticDocQA_energy":90.84,"ViDoRe_syntheticDocQA_government_reports":95.68,"ViDoRe_syntheticDocQA_healthcare_industry":97.09,"ViDoRe_esg_reports_human_labeled_v2":64.56,"ViDoRe_biomedical_lectures_v2_multilingual":68.23,"ViDoRe_economics_reports_v2_multilingual":63.09,"ViDoRe_esg_reports_v2_multilingual":65.49,"VisRAG_ArxivQA":83.58,"VisRAG_ChartQA":87.13,"VisRAG_MP-DocVQA":87.06,"VisRAG_SlideVQA":95.59,"VisRAG_InfoVQA":92.88,"VisRAG_PlotQA":72.33,"ViDoSeek-doc":85.0,"MMLongBench-doc":54.99,"ViDoSeek-page-fixed":81.94,"MMLongBench-page-fixed":55.73,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 11 |
+
{"Rank":11,"Models":"WeMM-Embedding-2B","Model Size(B)":2.13,"Date":"2025-12-16","Visdoc-Overall":79.85,"ViDoRe-V1":87.22,"ViDoRe-V2":53.4,"VisRAG":88.84,"VisDoc-OOD":68.89,"ViDoRe_arxivqa":90.25,"ViDoRe_docvqa":59.11,"ViDoRe_infovqa":91.2,"ViDoRe_tabfquad":89.41,"ViDoRe_tatdqa":73.81,"ViDoRe_shiftproject":82.61,"ViDoRe_syntheticDocQA_artificial_intelligence":98.15,"ViDoRe_syntheticDocQA_energy":94.08,"ViDoRe_syntheticDocQA_government_reports":95.35,"ViDoRe_syntheticDocQA_healthcare_industry":98.28,"ViDoRe_esg_reports_human_labeled_v2":54.54,"ViDoRe_biomedical_lectures_v2_multilingual":55.64,"ViDoRe_economics_reports_v2_multilingual":53.93,"ViDoRe_esg_reports_v2_multilingual":49.5,"VisRAG_ArxivQA":88.62,"VisRAG_ChartQA":88.61,"VisRAG_MP-DocVQA":91.01,"VisRAG_SlideVQA":95.83,"VisRAG_InfoVQA":93.74,"VisRAG_PlotQA":75.23,"ViDoSeek-doc":83.14,"MMLongBench-doc":54.65,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.27,"MMLongBench-page-old":16.53}
|
| 12 |
+
{"Rank":12,"Models":"RzenEmbed-v1-2B","Model Size(B)":2.21,"Date":"2025-07-16","Visdoc-Overall":79.4,"ViDoRe-V1":86.98,"ViDoRe-V2":57.63,"VisRAG":85.35,"VisDoc-OOD":67.11,"ViDoRe_arxivqa":83.4,"ViDoRe_docvqa":56.09,"ViDoRe_infovqa":89.89,"ViDoRe_tabfquad":94.39,"ViDoRe_tatdqa":69.32,"ViDoRe_shiftproject":89.88,"ViDoRe_syntheticDocQA_artificial_intelligence":98.76,"ViDoRe_syntheticDocQA_energy":92.78,"ViDoRe_syntheticDocQA_government_reports":97.19,"ViDoRe_syntheticDocQA_healthcare_industry":98.15,"ViDoRe_esg_reports_human_labeled_v2":58.93,"ViDoRe_biomedical_lectures_v2_multilingual":59.87,"ViDoRe_economics_reports_v2_multilingual":57.98,"ViDoRe_esg_reports_v2_multilingual":53.73,"VisRAG_ArxivQA":83.68,"VisRAG_ChartQA":86.39,"VisRAG_MP-DocVQA":85.54,"VisRAG_SlideVQA":94.07,"VisRAG_InfoVQA":91.92,"VisRAG_PlotQA":70.52,"ViDoSeek-doc":82.27,"MMLongBench-doc":51.95,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.89,"MMLongBench-page-old":16.21}
|
| 13 |
+
{"Rank":13,"Models":"<a href=\"https:\/\/seed1-6-embedding.github.io\">seed-1.6-embedding<\/a>","Model Size(B)":"unknown","Date":"2025-06-17","Visdoc-Overall":78.37,"ViDoRe-V1":85.53,"ViDoRe-V2":56.57,"VisRAG":84.74,"VisDoc-OOD":67.09,"ViDoRe_arxivqa":88.46,"ViDoRe_docvqa":60.36,"ViDoRe_infovqa":90.62,"ViDoRe_tabfquad":87.82,"ViDoRe_tatdqa":74.98,"ViDoRe_shiftproject":73.34,"ViDoRe_syntheticDocQA_artificial_intelligence":96.32,"ViDoRe_syntheticDocQA_energy":92.83,"ViDoRe_syntheticDocQA_government_reports":93.54,"ViDoRe_syntheticDocQA_healthcare_industry":97.05,"ViDoRe_esg_reports_human_labeled_v2":63.3,"ViDoRe_biomedical_lectures_v2_multilingual":57.14,"ViDoRe_economics_reports_v2_multilingual":53.85,"ViDoRe_esg_reports_v2_multilingual":51.99,"VisRAG_ArxivQA":85.79,"VisRAG_ChartQA":81.88,"VisRAG_MP-DocVQA":89.43,"VisRAG_SlideVQA":94.9,"VisRAG_InfoVQA":92.41,"VisRAG_PlotQA":64.02,"ViDoSeek-doc":82.57,"MMLongBench-doc":51.61,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.8,"MMLongBench-page-old":15.57}
|
| 14 |
+
{"Rank":14,"Models":"<a href=\"https:\/\/huggingface.co\/Haon-Chen\/e5-omni-3B\">e5-omni-3B<\/a>","Model Size(B)":3.0,"Date":"2026-01-09","Visdoc-Overall":78.11,"ViDoRe-V1":83.13,"ViDoRe-V2":59.53,"VisRAG":85.48,"VisDoc-OOD":68.07,"ViDoRe_arxivqa":82.2,"ViDoRe_docvqa":51.99,"ViDoRe_infovqa":88.88,"ViDoRe_tabfquad":88.86,"ViDoRe_tatdqa":58.78,"ViDoRe_shiftproject":80.14,"ViDoRe_syntheticDocQA_artificial_intelligence":98.15,"ViDoRe_syntheticDocQA_energy":93.17,"ViDoRe_syntheticDocQA_government_reports":93.21,"ViDoRe_syntheticDocQA_healthcare_industry":95.92,"ViDoRe_esg_reports_human_labeled_v2":61.84,"ViDoRe_biomedical_lectures_v2_multilingual":60.92,"ViDoRe_economics_reports_v2_multilingual":64.39,"ViDoRe_esg_reports_v2_multilingual":50.97,"VisRAG_ArxivQA":84.52,"VisRAG_ChartQA":86.75,"VisRAG_MP-DocVQA":85.51,"VisRAG_SlideVQA":95.4,"VisRAG_InfoVQA":92.55,"VisRAG_PlotQA":68.17,"ViDoSeek-doc":83.29,"MMLongBench-doc":52.85,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.38,"MMLongBench-page-old":15.0}
|
| 15 |
+
{"Rank":15,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-7B\">Ops-MM-embedding-v1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-07-02","Visdoc-Overall":74.99,"ViDoRe-V1":80.05,"ViDoRe-V2":59.59,"VisRAG":79.31,"VisDoc-OOD":67.49,"ViDoRe_arxivqa":78.17,"ViDoRe_docvqa":49.11,"ViDoRe_infovqa":86.59,"ViDoRe_tabfquad":91.4,"ViDoRe_tatdqa":55.59,"ViDoRe_shiftproject":76.17,"ViDoRe_syntheticDocQA_artificial_intelligence":90.99,"ViDoRe_syntheticDocQA_energy":87.53,"ViDoRe_syntheticDocQA_government_reports":91.56,"ViDoRe_syntheticDocQA_healthcare_industry":93.39,"ViDoRe_esg_reports_human_labeled_v2":66.27,"ViDoRe_biomedical_lectures_v2_multilingual":54.34,"ViDoRe_economics_reports_v2_multilingual":60.92,"ViDoRe_esg_reports_v2_multilingual":56.82,"VisRAG_ArxivQA":78.18,"VisRAG_ChartQA":79.53,"VisRAG_MP-DocVQA":78.2,"VisRAG_SlideVQA":91.11,"VisRAG_InfoVQA":87.16,"VisRAG_PlotQA":61.71,"ViDoSeek-doc":83.47,"MMLongBench-doc":51.51,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.47,"MMLongBench-page-old":15.89}
|
| 16 |
+
{"Rank":16,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-7B-Instruct\">gme-Qwen2-VL-7B-Instruct<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Visdoc-Overall":73.96,"ViDoRe-V1":89.55,"ViDoRe-V2":55.47,"VisRAG":84.95,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":87.53,"ViDoRe_docvqa":56.59,"ViDoRe_infovqa":92.17,"ViDoRe_tabfquad":92.71,"ViDoRe_tatdqa":76.58,"ViDoRe_shiftproject":95.64,"ViDoRe_syntheticDocQA_artificial_intelligence":99.63,"ViDoRe_syntheticDocQA_energy":95.69,"ViDoRe_syntheticDocQA_government_reports":99.5,"ViDoRe_syntheticDocQA_healthcare_industry":99.5,"ViDoRe_esg_reports_human_labeled_v2":62.76,"ViDoRe_biomedical_lectures_v2_multilingual":49.78,"ViDoRe_economics_reports_v2_multilingual":53.91,"ViDoRe_esg_reports_v2_multilingual":55.43,"VisRAG_ArxivQA":87.69,"VisRAG_ChartQA":81.29,"VisRAG_MP-DocVQA":89.08,"VisRAG_SlideVQA":94.72,"VisRAG_InfoVQA":93.49,"VisRAG_PlotQA":63.44,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":83.57,"MMLongBench-page-fixed":55.32,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 17 |
+
{"Rank":17,"Models":"Crotchet-embedding-2B","Model Size(B)":2.13,"Date":"2025-12-31","Visdoc-Overall":73.59,"ViDoRe-V1":78.16,"ViDoRe-V2":53.28,"VisRAG":82.21,"VisDoc-OOD":65.51,"ViDoRe_arxivqa":84.34,"ViDoRe_docvqa":42.93,"ViDoRe_infovqa":85.18,"ViDoRe_tabfquad":93.29,"ViDoRe_tatdqa":53.04,"ViDoRe_shiftproject":71.02,"ViDoRe_syntheticDocQA_artificial_intelligence":90.74,"ViDoRe_syntheticDocQA_energy":85.07,"ViDoRe_syntheticDocQA_government_reports":85.45,"ViDoRe_syntheticDocQA_healthcare_industry":90.59,"ViDoRe_esg_reports_human_labeled_v2":62.65,"ViDoRe_biomedical_lectures_v2_multilingual":46.92,"ViDoRe_economics_reports_v2_multilingual":51.47,"ViDoRe_esg_reports_v2_multilingual":52.09,"VisRAG_ArxivQA":81.64,"VisRAG_ChartQA":85.47,"VisRAG_MP-DocVQA":76.0,"VisRAG_SlideVQA":90.85,"VisRAG_InfoVQA":88.54,"VisRAG_PlotQA":70.74,"ViDoSeek-doc":81.84,"MMLongBench-doc":49.18,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":78.36,"MMLongBench-page-old":51.39}
|
| 18 |
+
{"Rank":18,"Models":"<a href=\"https:\/\/huggingface.co\/Alibaba-NLP\/gme-Qwen2-VL-2B-Instruct\">gme-Qwen2-VL-2B-Instruct<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Visdoc-Overall":71.88,"ViDoRe-V1":87.12,"ViDoRe-V2":53.88,"VisRAG":82.43,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":82.53,"ViDoRe_docvqa":55.16,"ViDoRe_infovqa":90.69,"ViDoRe_tabfquad":93.31,"ViDoRe_tatdqa":70.26,"ViDoRe_shiftproject":92.85,"ViDoRe_syntheticDocQA_artificial_intelligence":98.13,"ViDoRe_syntheticDocQA_energy":92.56,"ViDoRe_syntheticDocQA_government_reports":97.15,"ViDoRe_syntheticDocQA_healthcare_industry":98.52,"ViDoRe_esg_reports_human_labeled_v2":60.29,"ViDoRe_biomedical_lectures_v2_multilingual":53.99,"ViDoRe_economics_reports_v2_multilingual":50.8,"ViDoRe_esg_reports_v2_multilingual":50.43,"VisRAG_ArxivQA":81.95,"VisRAG_ChartQA":79.09,"VisRAG_MP-DocVQA":84.34,"VisRAG_SlideVQA":93.68,"VisRAG_InfoVQA":91.41,"VisRAG_PlotQA":64.12,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":79.81,"MMLongBench-page-fixed":51.32,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 19 |
+
{"Rank":19,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-7B\">UME-R1-7B<\/a>","Model Size(B)":8.29,"Date":"2025-10-20","Visdoc-Overall":71.71,"ViDoRe-V1":75.66,"ViDoRe-V2":50.53,"VisRAG":83.7,"VisDoc-OOD":58.3,"ViDoRe_arxivqa":73.56,"ViDoRe_docvqa":41.1,"ViDoRe_infovqa":80.83,"ViDoRe_tabfquad":90.24,"ViDoRe_tatdqa":46.67,"ViDoRe_shiftproject":64.96,"ViDoRe_syntheticDocQA_artificial_intelligence":89.47,"ViDoRe_syntheticDocQA_energy":85.7,"ViDoRe_syntheticDocQA_government_reports":89.82,"ViDoRe_syntheticDocQA_healthcare_industry":94.29,"ViDoRe_esg_reports_human_labeled_v2":50.41,"ViDoRe_biomedical_lectures_v2_multilingual":50.73,"ViDoRe_economics_reports_v2_multilingual":57.8,"ViDoRe_esg_reports_v2_multilingual":43.18,"VisRAG_ArxivQA":80.45,"VisRAG_ChartQA":84.95,"VisRAG_MP-DocVQA":83.43,"VisRAG_SlideVQA":91.47,"VisRAG_InfoVQA":89.2,"VisRAG_PlotQA":72.7,"ViDoSeek-doc":75.33,"MMLongBench-doc":41.28,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":21.28,"MMLongBench-page-old":12.32}
|
| 20 |
+
{"Rank":20,"Models":"<a href=\"https:\/\/huggingface.co\/OpenSearch-AI\/Ops-MM-embedding-v1-2B\">Ops-MM-embedding-v1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-07-02","Visdoc-Overall":71.48,"ViDoRe-V1":76.39,"ViDoRe-V2":53.18,"VisRAG":77.64,"VisDoc-OOD":65.09,"ViDoRe_arxivqa":73.72,"ViDoRe_docvqa":45.01,"ViDoRe_infovqa":81.41,"ViDoRe_tabfquad":88.81,"ViDoRe_tatdqa":49.59,"ViDoRe_shiftproject":72.57,"ViDoRe_syntheticDocQA_artificial_intelligence":89.8,"ViDoRe_syntheticDocQA_energy":84.27,"ViDoRe_syntheticDocQA_government_reports":87.06,"ViDoRe_syntheticDocQA_healthcare_industry":91.64,"ViDoRe_esg_reports_human_labeled_v2":58.57,"ViDoRe_biomedical_lectures_v2_multilingual":52.87,"ViDoRe_economics_reports_v2_multilingual":47.89,"ViDoRe_esg_reports_v2_multilingual":53.39,"VisRAG_ArxivQA":73.84,"VisRAG_ChartQA":80.17,"VisRAG_MP-DocVQA":75.06,"VisRAG_SlideVQA":89.15,"VisRAG_InfoVQA":86.66,"VisRAG_PlotQA":60.99,"ViDoSeek-doc":82.29,"MMLongBench-doc":47.89,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":21.44,"MMLongBench-page-old":13.06}
|
| 21 |
+
{"Rank":21,"Models":"colpali-v1.3","Model Size(B)":"unknown","Date":"2025-12-29","Visdoc-Overall":70.5,"ViDoRe-V1":84.57,"ViDoRe-V2":54.81,"VisRAG":81.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":83.33,"ViDoRe_docvqa":59.2,"ViDoRe_infovqa":85.38,"ViDoRe_tabfquad":86.63,"ViDoRe_tatdqa":70.47,"ViDoRe_shiftproject":76.83,"ViDoRe_syntheticDocQA_artificial_intelligence":96.26,"ViDoRe_syntheticDocQA_energy":95.02,"ViDoRe_syntheticDocQA_government_reports":95.59,"ViDoRe_syntheticDocQA_healthcare_industry":97.02,"ViDoRe_esg_reports_human_labeled_v2":57.25,"ViDoRe_biomedical_lectures_v2_multilingual":56.25,"ViDoRe_economics_reports_v2_multilingual":50.2,"ViDoRe_esg_reports_v2_multilingual":55.56,"VisRAG_ArxivQA":80.9,"VisRAG_ChartQA":77.04,"VisRAG_MP-DocVQA":87.03,"VisRAG_SlideVQA":95.13,"VisRAG_InfoVQA":85.73,"VisRAG_PlotQA":60.18,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":79.22,"MMLongBench-page-fixed":53.18,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 22 |
+
{"Rank":22,"Models":"<a href=\"https:\/\/huggingface.co\/zhibinlan\/UME-R1-2B\">UME-R1-2B<\/a>","Model Size(B)":2.21,"Date":"2025-10-20","Visdoc-Overall":68.16,"ViDoRe-V1":72.39,"ViDoRe-V2":46.16,"VisRAG":79.22,"VisDoc-OOD":57.78,"ViDoRe_arxivqa":73.86,"ViDoRe_docvqa":37.85,"ViDoRe_infovqa":76.19,"ViDoRe_tabfquad":86.11,"ViDoRe_tatdqa":40.63,"ViDoRe_shiftproject":66.79,"ViDoRe_syntheticDocQA_artificial_intelligence":85.87,"ViDoRe_syntheticDocQA_energy":83.25,"ViDoRe_syntheticDocQA_government_reports":82.56,"ViDoRe_syntheticDocQA_healthcare_industry":90.83,"ViDoRe_esg_reports_human_labeled_v2":50.16,"ViDoRe_biomedical_lectures_v2_multilingual":46.15,"ViDoRe_economics_reports_v2_multilingual":45.69,"ViDoRe_esg_reports_v2_multilingual":42.65,"VisRAG_ArxivQA":74.26,"VisRAG_ChartQA":85.98,"VisRAG_MP-DocVQA":75.59,"VisRAG_SlideVQA":87.11,"VisRAG_InfoVQA":84.38,"VisRAG_PlotQA":67.98,"ViDoSeek-doc":75.89,"MMLongBench-doc":39.68,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":21.2,"MMLongBench-page-old":11.9}
|
| 23 |
+
{"Rank":23,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-7B<\/a>","Model Size(B)":8.03,"Date":"2025-07-06","Visdoc-Overall":68.1,"ViDoRe-V1":70.68,"ViDoRe-V2":49.57,"VisRAG":79.45,"VisDoc-OOD":58.21,"ViDoRe_arxivqa":73.29,"ViDoRe_docvqa":38.27,"ViDoRe_infovqa":80.59,"ViDoRe_tabfquad":80.7,"ViDoRe_tatdqa":37.79,"ViDoRe_shiftproject":52.02,"ViDoRe_syntheticDocQA_artificial_intelligence":85.99,"ViDoRe_syntheticDocQA_energy":84.78,"ViDoRe_syntheticDocQA_government_reports":84.96,"ViDoRe_syntheticDocQA_healthcare_industry":88.37,"ViDoRe_esg_reports_human_labeled_v2":50.67,"ViDoRe_biomedical_lectures_v2_multilingual":50.89,"ViDoRe_economics_reports_v2_multilingual":54.38,"ViDoRe_esg_reports_v2_multilingual":42.33,"VisRAG_ArxivQA":73.96,"VisRAG_ChartQA":82.71,"VisRAG_MP-DocVQA":75.15,"VisRAG_SlideVQA":87.58,"VisRAG_InfoVQA":87.91,"VisRAG_PlotQA":69.42,"ViDoSeek-doc":73.82,"MMLongBench-doc":42.61,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.52,"MMLongBench-page-old":13.32}
|
| 24 |
+
{"Rank":24,"Models":"<a href=\"https:\/\/huggingface.co\/VLM2Vec\/VLM2Vec-V2.0\">VLM2Vec-V2.0-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Visdoc-Overall":63.56,"ViDoRe-V1":74.39,"ViDoRe-V2":44.61,"VisRAG":79.33,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":78.87,"ViDoRe_docvqa":37.06,"ViDoRe_infovqa":82.71,"ViDoRe_tabfquad":87.77,"ViDoRe_tatdqa":44.29,"ViDoRe_shiftproject":61.04,"ViDoRe_syntheticDocQA_artificial_intelligence":89.12,"ViDoRe_syntheticDocQA_energy":86.29,"ViDoRe_syntheticDocQA_government_reports":85.58,"ViDoRe_syntheticDocQA_healthcare_industry":91.13,"ViDoRe_esg_reports_human_labeled_v2":45.79,"ViDoRe_biomedical_lectures_v2_multilingual":44.59,"ViDoRe_economics_reports_v2_multilingual":42.33,"ViDoRe_esg_reports_v2_multilingual":45.74,"VisRAG_ArxivQA":76.74,"VisRAG_ChartQA":84.2,"VisRAG_MP-DocVQA":71.8,"VisRAG_SlideVQA":91.44,"VisRAG_InfoVQA":85.88,"VisRAG_PlotQA":65.91,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":80.3,"MMLongBench-page-fixed":44.7,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 25 |
+
{"Rank":25,"Models":"<a href=\"https:\/\/github.com\/GaryGuTC\/UniME-v2\">UniME-V2-LLaVA-OneVision-7B<\/a>","Model Size(B)":8.03,"Date":"2025-10-15","Visdoc-Overall":60.24,"ViDoRe-V1":61.76,"ViDoRe-V2":42.0,"VisRAG":70.53,"VisDoc-OOD":58.3,"ViDoRe_arxivqa":51.9,"ViDoRe_docvqa":38.17,"ViDoRe_infovqa":73.16,"ViDoRe_tabfquad":57.75,"ViDoRe_tatdqa":35.48,"ViDoRe_shiftproject":45.42,"ViDoRe_syntheticDocQA_artificial_intelligence":76.85,"ViDoRe_syntheticDocQA_energy":77.27,"ViDoRe_syntheticDocQA_government_reports":79.87,"ViDoRe_syntheticDocQA_healthcare_industry":81.71,"ViDoRe_esg_reports_human_labeled_v2":54.67,"ViDoRe_biomedical_lectures_v2_multilingual":33.75,"ViDoRe_economics_reports_v2_multilingual":35.95,"ViDoRe_esg_reports_v2_multilingual":43.63,"VisRAG_ArxivQA":53.13,"VisRAG_ChartQA":83.67,"VisRAG_MP-DocVQA":66.4,"VisRAG_SlideVQA":86.44,"VisRAG_InfoVQA":82.58,"VisRAG_PlotQA":50.96,"ViDoSeek-doc":75.79,"MMLongBench-doc":40.8,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":22.89,"MMLongBench-page-old":11.96}
|
| 26 |
+
{"Rank":26,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2503.19900\">interestFM-UIR-CAFe-0.5B<\/a>","Model Size(B)":0.894,"Date":"2025-07-06","Visdoc-Overall":54.83,"ViDoRe-V1":56.93,"ViDoRe-V2":32.59,"VisRAG":68.57,"VisDoc-OOD":47.59,"ViDoRe_arxivqa":51.19,"ViDoRe_docvqa":25.46,"ViDoRe_infovqa":71.95,"ViDoRe_tabfquad":59.64,"ViDoRe_tatdqa":27.05,"ViDoRe_shiftproject":31.8,"ViDoRe_syntheticDocQA_artificial_intelligence":78.74,"ViDoRe_syntheticDocQA_energy":70.75,"ViDoRe_syntheticDocQA_government_reports":75.47,"ViDoRe_syntheticDocQA_healthcare_industry":77.29,"ViDoRe_esg_reports_human_labeled_v2":36.24,"ViDoRe_biomedical_lectures_v2_multilingual":29.72,"ViDoRe_economics_reports_v2_multilingual":37.61,"ViDoRe_esg_reports_v2_multilingual":26.78,"VisRAG_ArxivQA":57.82,"VisRAG_ChartQA":75.62,"VisRAG_MP-DocVQA":63.24,"VisRAG_SlideVQA":82.32,"VisRAG_InfoVQA":80.28,"VisRAG_PlotQA":52.14,"ViDoSeek-doc":61.41,"MMLongBench-doc":33.78,"ViDoSeek-page-fixed":"\u26a0\ufe0f! Please fix this score!","MMLongBench-page-fixed":"\u26a0\ufe0f! Please fix this score!","ViDoSeek-page-old":17.62,"MMLongBench-page-old":9.95}
|
| 27 |
+
{"Rank":27,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret-Qwen2.5VL-7b\">LamRA-Ret-Qwen2.5VL-7b<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Visdoc-Overall":47.61,"ViDoRe-V1":56.4,"ViDoRe-V2":33.62,"VisRAG":58.15,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":53.04,"ViDoRe_docvqa":25.42,"ViDoRe_infovqa":72.19,"ViDoRe_tabfquad":66.51,"ViDoRe_tatdqa":26.01,"ViDoRe_shiftproject":28.13,"ViDoRe_syntheticDocQA_artificial_intelligence":70.31,"ViDoRe_syntheticDocQA_energy":66.33,"ViDoRe_syntheticDocQA_government_reports":72.21,"ViDoRe_syntheticDocQA_healthcare_industry":83.8,"ViDoRe_esg_reports_human_labeled_v2":32.98,"ViDoRe_biomedical_lectures_v2_multilingual":35.87,"ViDoRe_economics_reports_v2_multilingual":32.37,"ViDoRe_esg_reports_v2_multilingual":33.26,"VisRAG_ArxivQA":38.03,"VisRAG_ChartQA":65.21,"VisRAG_MP-DocVQA":54.14,"VisRAG_SlideVQA":76.55,"VisRAG_InfoVQA":73.5,"VisRAG_PlotQA":41.46,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":68.54,"MMLongBench-page-fixed":35.83,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 28 |
+
{"Rank":28,"Models":"<a href=\"https:\/\/huggingface.co\/code-kunkun\/LamRA-Ret\">LamRA-Ret<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Visdoc-Overall":27.72,"ViDoRe-V1":33.83,"ViDoRe-V2":11.53,"VisRAG":37.56,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":31.54,"ViDoRe_docvqa":19.85,"ViDoRe_infovqa":63.67,"ViDoRe_tabfquad":53.47,"ViDoRe_tatdqa":7.88,"ViDoRe_shiftproject":15.95,"ViDoRe_syntheticDocQA_artificial_intelligence":29.83,"ViDoRe_syntheticDocQA_energy":36.05,"ViDoRe_syntheticDocQA_government_reports":41.18,"ViDoRe_syntheticDocQA_healthcare_industry":38.83,"ViDoRe_esg_reports_human_labeled_v2":6.91,"ViDoRe_biomedical_lectures_v2_multilingual":13.42,"ViDoRe_economics_reports_v2_multilingual":19.37,"ViDoRe_esg_reports_v2_multilingual":6.43,"VisRAG_ArxivQA":2.04,"VisRAG_ChartQA":42.74,"VisRAG_MP-DocVQA":33.37,"VisRAG_SlideVQA":56.3,"VisRAG_InfoVQA":56.86,"VisRAG_PlotQA":34.06,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":34.48,"MMLongBench-page-fixed":18.29,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 29 |
+
{"Rank":29,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-7B\">VLM2Vec-V1-Qwen2VL-7B<\/a>","Model Size(B)":8.29,"Date":"2025-12-29","Visdoc-Overall":26.82,"ViDoRe-V1":19.99,"ViDoRe-V2":9.24,"VisRAG":58.85,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":28.16,"ViDoRe_docvqa":18.98,"ViDoRe_infovqa":44.77,"ViDoRe_tabfquad":16.98,"ViDoRe_tatdqa":5.73,"ViDoRe_shiftproject":1.63,"ViDoRe_syntheticDocQA_artificial_intelligence":18.23,"ViDoRe_syntheticDocQA_energy":23.9,"ViDoRe_syntheticDocQA_government_reports":13.88,"ViDoRe_syntheticDocQA_healthcare_industry":27.61,"ViDoRe_esg_reports_human_labeled_v2":6.95,"ViDoRe_biomedical_lectures_v2_multilingual":5.22,"ViDoRe_economics_reports_v2_multilingual":13.75,"ViDoRe_esg_reports_v2_multilingual":11.05,"VisRAG_ArxivQA":52.85,"VisRAG_ChartQA":68.96,"VisRAG_MP-DocVQA":52.74,"VisRAG_SlideVQA":72.76,"VisRAG_InfoVQA":71.3,"VisRAG_PlotQA":34.52,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":77.4,"MMLongBench-page-fixed":36.76,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 30 |
+
{"Rank":30,"Models":"<a href=\"https:\/\/huggingface.co\/TIGER-Lab\/VLM2Vec-Qwen2VL-2B\">VLM2Vec-V1-Qwen2VL-2B<\/a>","Model Size(B)":2.21,"Date":"2025-12-29","Visdoc-Overall":26.0,"ViDoRe-V1":20.59,"ViDoRe-V2":13.19,"VisRAG":52.23,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":18.12,"ViDoRe_docvqa":14.01,"ViDoRe_infovqa":39.53,"ViDoRe_tabfquad":36.03,"ViDoRe_tatdqa":10.49,"ViDoRe_shiftproject":8.41,"ViDoRe_syntheticDocQA_artificial_intelligence":17.04,"ViDoRe_syntheticDocQA_energy":16.35,"ViDoRe_syntheticDocQA_government_reports":25.15,"ViDoRe_syntheticDocQA_healthcare_industry":20.79,"ViDoRe_esg_reports_human_labeled_v2":13.05,"ViDoRe_biomedical_lectures_v2_multilingual":6.51,"ViDoRe_economics_reports_v2_multilingual":12.86,"ViDoRe_esg_reports_v2_multilingual":20.32,"VisRAG_ArxivQA":41.22,"VisRAG_ChartQA":59.48,"VisRAG_MP-DocVQA":43.55,"VisRAG_SlideVQA":74.5,"VisRAG_InfoVQA":71.1,"VisRAG_PlotQA":23.51,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":67.81,"MMLongBench-page-fixed":26.04,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 31 |
+
{"Rank":31,"Models":"dp-embedding-v3-lite","Model Size(B)":8.29,"Date":"2025-12-15","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 32 |
+
{"Rank":32,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-2B<\/a>","Model Size(B)":2.21,"Date":"2025-11-24","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 33 |
+
{"Rank":33,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-3B<\/a>","Model Size(B)":3.75,"Date":"2025-11-24","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 34 |
+
{"Rank":34,"Models":"TCE-v1","Model Size(B)":8.0,"Date":"2025-10-31","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 35 |
+
{"Rank":35,"Models":"UniVec-CoT-7B","Model Size(B)":8.29,"Date":"unknown","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 36 |
+
{"Rank":36,"Models":"<a href=\"https:\/\/arxiv.org\/abs\/2511.19278\">ReMatch-7B<\/a>","Model Size(B)":8.29,"Date":"2025-11-24","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 37 |
+
{"Rank":37,"Models":"UniVec-7B","Model Size(B)":8.29,"Date":"unknown","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 38 |
+
{"Rank":38,"Models":"ReCo-7B","Model Size(B)":8.29,"Date":"2025-08-15","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 39 |
+
{"Rank":39,"Models":"OEmbedding-v1-7B","Model Size(B)":8.29,"Date":"2025-10-14","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 40 |
+
{"Rank":40,"Models":"<a href=\"https:\/\/github.com\/QQ-MM\/QQMM-embed\">QQMM-embed-v2<\/a>","Model Size(B)":8.29,"Date":"2025-09-15","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 41 |
+
{"Rank":41,"Models":"QQMM-embed-v3","Model Size(B)":8.29,"Date":"2025-12-30","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
|
| 42 |
+
{"Rank":42,"Models":"TCR","Model Size(B)":8.77,"Date":"2026-01-15","Visdoc-Overall":0.0,"ViDoRe-V1":0.0,"ViDoRe-V2":0.0,"VisRAG":0.0,"VisDoc-OOD":0.0,"ViDoRe_arxivqa":0.0,"ViDoRe_docvqa":0.0,"ViDoRe_infovqa":0.0,"ViDoRe_tabfquad":0.0,"ViDoRe_tatdqa":0.0,"ViDoRe_shiftproject":0.0,"ViDoRe_syntheticDocQA_artificial_intelligence":0.0,"ViDoRe_syntheticDocQA_energy":0.0,"ViDoRe_syntheticDocQA_government_reports":0.0,"ViDoRe_syntheticDocQA_healthcare_industry":0.0,"ViDoRe_esg_reports_human_labeled_v2":0.0,"ViDoRe_biomedical_lectures_v2_multilingual":0.0,"ViDoRe_economics_reports_v2_multilingual":0.0,"ViDoRe_esg_reports_v2_multilingual":0.0,"VisRAG_ArxivQA":0.0,"VisRAG_ChartQA":0.0,"VisRAG_MP-DocVQA":0.0,"VisRAG_SlideVQA":0.0,"VisRAG_InfoVQA":0.0,"VisRAG_PlotQA":0.0,"ViDoSeek-doc":0.0,"MMLongBench-doc":0.0,"ViDoSeek-page-fixed":0.0,"MMLongBench-page-fixed":0.0,"ViDoSeek-page-old":"\u2705","MMLongBench-page-old":"\u2705"}
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@@ -27,15 +27,14 @@ training, and 16 out-of-distribution datasets, reserved for evaluation.
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Building upon on **MMEB-V1**, **MMEB-V2** expands the evaluation scope to include five new tasks: four video-based tasks
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— Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval.
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-
This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings.
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<
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<summary><span style='font-weight:bold'>🔥 What's NEW: The leaderboards' rankings can be directly downloaded now. Go to Files: rankings/ folder and select the leaderboard you want to download</span></summary>
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<ul>
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<li>[
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<li>[2025-06] MMEB-V2 released!</li>
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</ul
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</details>
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| [**📈Overview**](https://tiger-ai-lab.github.io/VLM2Vec/) | [**Github**](https://github.com/TIGER-AI-Lab/VLM2Vec)
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| [**📖MMEB-V2/VLM2Vec-V2 Paper**](https://arxiv.org/abs/2507.04590)
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@@ -46,10 +45,10 @@ This comprehensive suite enables robust evaluation of multimodal embedding model
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LEADERBOARD_INFO = f"""
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## Dataset Overview
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<
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-
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-
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-
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This is the dictionary of all datasets used in our code. Please make sure all datasets' scores are included in your submission. \n
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```python
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{pp.pformat(DATASETS)}
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| 27 |
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| 28 |
Building upon on **MMEB-V1**, **MMEB-V2** expands the evaluation scope to include five new tasks: four video-based tasks
|
| 29 |
— Video Retrieval, Moment Retrieval, Video Classification, and Video Question Answering — and one task focused on visual documents, Visual Document Retrieval.
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| 30 |
+
This comprehensive suite enables robust evaluation of multimodal embedding models across static, temporal, and structured visual data settings. \n
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| 31 |
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+
<summary><span style='font-weight:bold'>🔥 What's NEW: </span></summary>
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<ul>
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+
<li> [2026-01] We have fixed the error found in ViDoSeek-page and MMLongBench-page (See this [GitHub issue](https://github.com/TIGER-AI-Lab/VLM2Vec/issues/167) for more info). We kindly ask the authors to rerun their models on the visdoc datasets and update your scores on the leaderboard. We appreciate your cooperations!
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<li>[2025-11] The leaderboards' rankings can be directly downloaded in csv/json format. Scroll down to the bottom of each tab and click the download button.</li>
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<li>[2025-06] MMEB-V2 released!</li>
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+
</ul>
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| 38 |
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| [**📈Overview**](https://tiger-ai-lab.github.io/VLM2Vec/) | [**Github**](https://github.com/TIGER-AI-Lab/VLM2Vec)
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| [**📖MMEB-V2/VLM2Vec-V2 Paper**](https://arxiv.org/abs/2507.04590)
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LEADERBOARD_INFO = f"""
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## Dataset Overview
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<summary>Visual Overview</summary>
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See above image for a visual overview of the datasets included in MMEB. \n
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The scores used in MMEB-V2 leaderboard are unweighted average of all the datasets. \n
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See calculate_score() in utils_v2.py line 89 for more details. \n
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This is the dictionary of all datasets used in our code. Please make sure all datasets' scores are included in your submission. \n
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```python
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{pp.pformat(DATASETS)}
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utils_v2.py
CHANGED
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@@ -1,33 +1,34 @@
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import json
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import os
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import pandas as pd
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from utils import create_hyperlinked_names, process_model_size
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from datasets import *
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-
BASE_COLS = ['Rank', 'Models', 'Model Size(B)']
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BASE_DATA_TITLE_TYPE = ['number', 'markdown', 'str', '
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COLUMN_NAMES = BASE_COLS + ["Overall", 'Image-Overall', 'Video-Overall', 'Visdoc-Overall']
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DATA_TITLE_TYPE = BASE_DATA_TITLE_TYPE + \
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['number'] *
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SUB_TASKS_I = ["I-CLS", "I-QA", "I-RET", "I-VG"]
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TASKS_I = ['Image-Overall'] + SUB_TASKS_I + ALL_DATASETS_SPLITS['image']
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COLUMN_NAMES_I = BASE_COLS + TASKS_I
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DATA_TITLE_TYPE_I = BASE_DATA_TITLE_TYPE + \
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-
['number'] * len(TASKS_I
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SUB_TASKS_V = ["V-CLS", "V-QA", "V-RET", "V-MRET"]
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TASKS_V = ['Video-Overall'] + SUB_TASKS_V + ALL_DATASETS_SPLITS['video']
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COLUMN_NAMES_V = BASE_COLS + TASKS_V
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DATA_TITLE_TYPE_V = BASE_DATA_TITLE_TYPE + \
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['number'] * len(TASKS_V
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SUB_TASKS_D = ['ViDoRe-V1', 'ViDoRe-V2', 'VisRAG', 'VisDoc-OOD']
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TASKS_D = ['Visdoc-Overall'] + SUB_TASKS_D + ALL_DATASETS_SPLITS['visdoc']
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COLUMN_NAMES_D = BASE_COLS + TASKS_D
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DATA_TITLE_TYPE_D = BASE_DATA_TITLE_TYPE + \
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-
['number'] * len(TASKS_D
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TABLE_INTRODUCTION = """**MMEB**: Massive MultiModal Embedding Benchmark \n
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Models are ranked based on **Overall**"""
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@@ -39,8 +40,9 @@ TABLE_INTRODUCTION_I = """**I-CLS**: Image Classification, **I-QA**: (Image) Vis
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TABLE_INTRODUCTION_V = """**V-CLS**: Video Classification, **V-QA**: (Video) Visual Question Answering, **V-RET**: Video Retrieval, **V-MRET**: Video Moment Retrieval \n
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Models are ranked based on **Video-Overall**"""
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TABLE_INTRODUCTION_D = """**VisDoc**: Visual Document Understanding \n
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Models are ranked based on **Visdoc-Overall**
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-
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LEADERBOARD_INFO = """
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## Dataset Summary
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"""
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@@ -74,6 +76,10 @@ def load_scores(raw_scores=None):
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all_scores = {}
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for modality, datasets_list in DATASETS.items(): # Ex.: ('image', {'I-CLS': [...], 'I-QA': [...]})
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for sub_task, datasets in datasets_list.items(): # Ex.: ('I-CLS', ['VOC2007', 'N24News', ...])
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for dataset in datasets: # Ex.: 'VOC2007'
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score = raw_scores.get(modality, {}).get(dataset, 0.0)
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score = 0.0 if isinstance(score, str) and "N/A" in score else score
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@@ -123,11 +129,19 @@ def generate_model_row(data):
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'Model Size(B)': metadata.get('model_size', None),
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'URL': metadata.get('url', None),
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'Data Source': metadata.get('data_source', 'Self-Reported'),
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}
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scores = calculate_score(data['metrics'])
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row.update(scores)
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return row
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def rank_models(df, column='Overall', rank_name='Rank'):
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"""Ranks the models based on the specific score."""
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df = df.sort_values(by=column, ascending=False).reset_index(drop=True)
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@@ -140,6 +154,7 @@ def get_df():
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rows = [generate_model_row(data) for data in all_data]
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df = pd.DataFrame(rows)
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df['Model Size(B)'] = df['Model Size(B)'].apply(process_model_size)
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df = create_hyperlinked_names(df)
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df = rank_models(df, column='Overall')
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return df
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@@ -162,12 +177,13 @@ def search_and_filter_models(df, query, min_size, max_size):
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return filtered_df[COLUMN_NAMES]
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| 165 |
-
def save_ranking_summary(df, name, dir='rankings'):
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csv_path, json_path = os.path.join(dir, f'{name}.csv'), os.path.join(dir, f'{name}.jsonl')
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-
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-
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return csv_path, json_path
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def download_ranking(df, name, format='csv', dir='rankings'):
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csv_path, json_path = save_ranking_summary(df, name, dir)
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return csv_path if format == 'csv' else json_path
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import json
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import os
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import pandas as pd
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+
from datetime import datetime
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from utils import create_hyperlinked_names, process_model_size
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from datasets import *
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+
BASE_COLS = ['Rank', 'Models', 'Model Size(B)', 'Date']
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+
BASE_DATA_TITLE_TYPE = ['number', 'markdown', 'str', 'str']
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COLUMN_NAMES = BASE_COLS + ["Overall", 'Image-Overall', 'Video-Overall', 'Visdoc-Overall']
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DATA_TITLE_TYPE = BASE_DATA_TITLE_TYPE + \
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+
['number'] * 4
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| 15 |
SUB_TASKS_I = ["I-CLS", "I-QA", "I-RET", "I-VG"]
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TASKS_I = ['Image-Overall'] + SUB_TASKS_I + ALL_DATASETS_SPLITS['image']
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COLUMN_NAMES_I = BASE_COLS + TASKS_I
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| 18 |
DATA_TITLE_TYPE_I = BASE_DATA_TITLE_TYPE + \
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+
['number'] * len(TASKS_I)
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| 20 |
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| 21 |
SUB_TASKS_V = ["V-CLS", "V-QA", "V-RET", "V-MRET"]
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| 22 |
TASKS_V = ['Video-Overall'] + SUB_TASKS_V + ALL_DATASETS_SPLITS['video']
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| 23 |
COLUMN_NAMES_V = BASE_COLS + TASKS_V
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| 24 |
DATA_TITLE_TYPE_V = BASE_DATA_TITLE_TYPE + \
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| 25 |
+
['number'] * len(TASKS_V)
|
| 26 |
|
| 27 |
SUB_TASKS_D = ['ViDoRe-V1', 'ViDoRe-V2', 'VisRAG', 'VisDoc-OOD']
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| 28 |
TASKS_D = ['Visdoc-Overall'] + SUB_TASKS_D + ALL_DATASETS_SPLITS['visdoc']
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| 29 |
COLUMN_NAMES_D = BASE_COLS + TASKS_D
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| 30 |
DATA_TITLE_TYPE_D = BASE_DATA_TITLE_TYPE + \
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| 31 |
+
['number'] * len(TASKS_D)
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| 32 |
|
| 33 |
TABLE_INTRODUCTION = """**MMEB**: Massive MultiModal Embedding Benchmark \n
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Models are ranked based on **Overall**"""
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| 40 |
TABLE_INTRODUCTION_V = """**V-CLS**: Video Classification, **V-QA**: (Video) Visual Question Answering, **V-RET**: Video Retrieval, **V-MRET**: Video Moment Retrieval \n
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| 41 |
Models are ranked based on **Video-Overall**"""
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| 42 |
TABLE_INTRODUCTION_D = """**VisDoc**: Visual Document Understanding \n
|
| 43 |
+
Models are ranked based on **Visdoc-Overall** \n
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| 44 |
+
**⚠️ Your Attention Please! We have fixed the error found in the eval code of ViDoSeek-page and MMLongBench-page (See this [GitHub issue](https://github.com/TIGER-AI-Lab/VLM2Vec/issues/167) for more info), and the two datasets' scores have been temporarily removed from the leaderboard. We have added two new columns to the leaderboard, ViDoSeek-page-fixed and MMLongBench-page-fixed. The scores of models submitted before --JANURARY 2026-- have been changed to ViDoSeek-page-old and MMLongBench-page-old, and will be replaced after a new submission. Here is the [list of models](https://huggingface.co/spaces/TIGER-Lab/MMEB-Leaderboard/blob/main/archive/page_old_scores.jsonl) that has to be fixed. We kindly ask the authors on this list to rerun their models on the visdoc datasets and re-submit a PR with your fixed scores. (Note: If you see a ⚠️ in your model's score, please rerun your model and re-submit your scores, and then your old scores will be placed a ✅ to indicate a fixed version.) We appreciate your cooperations!**"""
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+
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| 46 |
LEADERBOARD_INFO = """
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| 47 |
## Dataset Summary
|
| 48 |
"""
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|
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|
| 76 |
all_scores = {}
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| 77 |
for modality, datasets_list in DATASETS.items(): # Ex.: ('image', {'I-CLS': [...], 'I-QA': [...]})
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| 78 |
for sub_task, datasets in datasets_list.items(): # Ex.: ('I-CLS', ['VOC2007', 'N24News', ...])
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+
# ========================= HARD CODED TEMPORARY FIX =================
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| 80 |
+
if modality == 'visdoc' and sub_task == 'VisDoc-OOD':
|
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+
datasets = datasets + ['ViDoSeek-page', 'MMLongBench-page']
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+
# ====================================================================
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for dataset in datasets: # Ex.: 'VOC2007'
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score = raw_scores.get(modality, {}).get(dataset, 0.0)
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score = 0.0 if isinstance(score, str) and "N/A" in score else score
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'Model Size(B)': metadata.get('model_size', None),
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'URL': metadata.get('url', None),
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'Data Source': metadata.get('data_source', 'Self-Reported'),
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+
'Date': metadata.get('report_generated_date', None)
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}
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scores = calculate_score(data['metrics'])
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row.update(scores)
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return row
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+
def print_time(time: str|None):
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+
try:
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| 140 |
+
dt = datetime.strptime(time, "%Y-%m-%dT%H:%M:%S.%f")
|
| 141 |
+
return dt.strftime("%Y-%m-%d")
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| 142 |
+
except (ValueError, TypeError):
|
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+
return 'unknown'
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+
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def rank_models(df, column='Overall', rank_name='Rank'):
|
| 146 |
"""Ranks the models based on the specific score."""
|
| 147 |
df = df.sort_values(by=column, ascending=False).reset_index(drop=True)
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| 154 |
rows = [generate_model_row(data) for data in all_data]
|
| 155 |
df = pd.DataFrame(rows)
|
| 156 |
df['Model Size(B)'] = df['Model Size(B)'].apply(process_model_size)
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| 157 |
+
df['Date'] = df['Date'].apply(print_time)
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df = create_hyperlinked_names(df)
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| 159 |
df = rank_models(df, column='Overall')
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return df
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return filtered_df[COLUMN_NAMES]
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+
def save_ranking_summary(df, name, save_now=True, dir='rankings'):
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csv_path, json_path = os.path.join(dir, f'{name}.csv'), os.path.join(dir, f'{name}.jsonl')
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+
if save_now:
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| 183 |
+
df.to_csv(csv_path, index=False)
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| 184 |
+
df.to_json(json_path, orient='records', lines=True)
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return csv_path, json_path
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| 187 |
def download_ranking(df, name, format='csv', dir='rankings'):
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+
csv_path, json_path = save_ranking_summary(df, name, save_now=False, dir=dir)
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| 189 |
return csv_path if format == 'csv' else json_path
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