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Models/InternVL2.5-26B

InternVL2.5-26B

Reported on 12 benchmarks across 2 tasks · 1 paper · 1 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing12 results

  • Visual Question Answering (VQA)onVLM2-Bench
    PC-grp· 2024-12-06
    61
    best: 69 (Qwen2.5-VL-7B)
    SOTA
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    Average Score on VLM2-bench (9 subtasks)· 2024-12-06
    45.59
    best: 60.36 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    GC-mat· 2024-12-06
    30.5
    best: 37.45 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    GC-trk· 2024-12-06
    30.59
    best: 43.38 (Qwen2.5-VL-7B)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    OC-cnt· 2024-12-06
    51.48
    best: 80.62 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    OC-cpr· 2024-12-06
    43.33
    best: 74.17 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    OC-grp· 2024-12-06
    52.5
    best: 57.5 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    PC-VID· 2024-12-06
    21.75
    best: 66.75 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    PC-cnt· 2024-12-06
    59.7
    best: 90.5 (GPT-4o)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onVLM2-Bench
    PC-cpr· 2024-12-06
    59.5
    best: 80 (Qwen2.5-VL-7B)
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question Answering (VQA)onMM-Vet
    GPT-4 score· 2024-12-06
    65
    best: 74.24 (MMCTAgent (GPT-4 + GPT-4V))
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271
  • Visual Question AnsweringonMM-Vet
    GPT-4 score· 2024-12-06
    65
    best: 74.24 (MMCTAgent (GPT-4 + GPT-4V))
    Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271