DanQing100M: 100 Million Chinese Image-Text Pairs for Vision-Language Pre-training

DanQing100M is a large-scale Chinese vision-language dataset containing 100 million image-text pairs, totaling 12 terabytes. It was created by researchers including Hengyu Shen, Tiancheng Gu, and others from DeepGlint-AI, using web data from 2024 to 2025. The dataset is intended for vision-language pre-training tasks.

Use Cases

• Train vision-language models based on the 100 million Chinese image-text pairs.
• Fine-tune Chinese multimodal models for tasks like image captioning based on web-sourced data.
• Benchmark model performance on large-scale Chinese vision-language understanding tasks.
• Conduct research on cross-modal alignment for Chinese language and imagery.

Strengths

• Contains 100 million image-text pairs, a large-scale resource.
• Dataset size is 12 terabytes, indicating high-resolution or diverse content.
• Data is sourced from recent web data (2024-2025), suggesting contemporary relevance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• License information is unknown, which may restrict usage.

Provenance

Source

DeepGlint-AI

Collection Method

Likely gathered from web sources.

Time Range

2024-2025

Freshness

Last updated 2026-03-25 03:26:02; freshness should be verified.

Geography

China (implied by Chinese language focus)