metadata
language:
- en
license: apache-2.0
task_categories:
- visual-question-answering
- multiple-choice
tags:
- mmbench
- multimodal
- vlm-eval
size_categories:
- 1K<n<10K
configs:
- config_name: all
data_files:
- split: dev
path: all/dev-*
- config_name: coarse_perception
data_files:
- split: dev
path: coarse_perception/dev-*
- config_name: finegrained_perception_single_instance
data_files:
- split: dev
path: finegrained_perception_single_instance/dev-*
- config_name: finegrained_perception_cross_instance
data_files:
- split: dev
path: finegrained_perception_cross_instance/dev-*
- config_name: attribute_reasoning
data_files:
- split: dev
path: attribute_reasoning/dev-*
- config_name: relation_reasoning
data_files:
- split: dev
path: relation_reasoning/dev-*
- config_name: logic_reasoning
data_files:
- split: dev
path: logic_reasoning/dev-*
MMBench EN Dev V1.0 — split by L2 category
The MMBench-EN-Dev-V1.0 dev split, pre-split into 6 subsets by the original l2-category field for convenient browsing in the dataset viewer.
- Source: official OpenCompass TSV
MMBench_DEV_EN.tsv - MD5 (verified):
b6caf1133a01c6bb705cf753bb527ed8— matches the value registered in VLMEvalKit. - Rows: 4,329
- Format note: the source TSV uses VLMEvalKit's compressed CircularEval format where many rows reference another row's image by
indexinstead of storing base64. References are resolved here, so every row carries its own decodedimage.
Subsets
| Config | Source l2-category |
# samples |
|---|---|---|
all |
(everything) | 4,329 |
coarse_perception |
coarse_perception |
1,109 |
finegrained_perception_single_instance |
finegrained_perception (instance-level) |
1,131 |
finegrained_perception_cross_instance |
finegrained_perception (cross-instance) |
533 |
attribute_reasoning |
attribute_reasoning |
699 |
relation_reasoning |
relation_reasoning |
445 |
logic_reasoning |
logic_reasoning |
412 |
Each subset has a single split: dev. The L3 ability ladder (20 fine-grained classes) is preserved in the category column.
Columns
index, question, hint, A, B, C, D, answer, category (L3, 20 classes), image (PIL), l2-category (L2, 6 classes), split, source, comment.
Usage
from datasets import load_dataset
ds = load_dataset("Ryoo72/MMBench-EN-Dev-V10", "all", split="dev")
ds_logic = load_dataset("Ryoo72/MMBench-EN-Dev-V10", "logic_reasoning", split="dev")