LLM Datasets

7 million global genuine high-quality videos. All are genuine video works released by photographers around the world. 6 million of them are described in English and 1 million in Chinese. They cover a variety of categories such as people, landscapes, animals, etc. The resolution is above 1080p.

300 Million Pairs of High-Quality Image-Caption Dataset includes a large-scale collection of photographic and vector images paired with English textual descriptions. The complete image library comprises nearly 300 million images, with a curated subset of 100 million high-quality image-caption pairs available for generative AI and vision-language model training. All images are authentic and legally licensed works created by professional photographers. The dataset primarily features English captions with minimal Chinese, offering diverse scenes, objects, and compositions suitable for tasks such as image captioning, visual question answering (VQA), image-text retrieval, and multimodal foundation model pretraining. The dataset supports large-scale LLM and VLM applications and complies with global data privacy and copyright regulations, including GDPR, CCPA, and PIPL.

Massive 3D Models & Scenes Dataset includes 270 million sets of 3D models and 18 million 3D scenes. 3D models cover conventional models, interactive models, and physics-enhanced models with various objects in indoor residential environments. 3D scenes cover indoor home decoration scenarios and commercial space environments. This dataset can be used for tasks like 3D asset generation, virtual environment simulation, AI model training, and industrial design applications.

This dataset includes high-quality video data of 25,000 unique individuals, captured in a variety of styles and environmental settings. Each person ID is represented with identity-consistent video samples featuring diverse skin tones, including White, Asian, Black, and Brown, and a wide age range from youth to elderly. All videos are at least 1080p in resolution and longer than 10 seconds in duration. This dataset is ideal for training AI models in digital human creation, identity-preserving video generation, character reanimation, and virtual avatar modeling. The diversity and consistency make it highly suitable for generative AI applications. All data was collected ethically and complies with global privacy laws including GDPR, CCPA, and PIPL.

This dataset is collected from the Japanese OKWAVE Q&A platform and includes large-scale parsed and processed text data suitable for LLM training and Japanese natural language understanding. It contains structured fields such as questions, answers, categories, timestamps, user metadata, and supplementary explanations. As of April 2025, the dataset includes 8.4 million questions with 2.3 billion words, 27 million answers totaling 7.6 billion words, 15.5 million thank-you messages (1.7 billion words), and 2.1 million supplementary replies (360 million words). Continuously updated and rich in user-generated content, this dataset is ideal for building Japanese conversational AI, ChatGPT fine-tuning, question answering systems, text summarization, and semantic parsing models. All data complies with relevant data usage and privacy regulations.

50,538 Images - OCR Dataset_Exam Questions, covering multiple subjects, question types and collection devices (mobile phones, scanners), and the text was transcribed, and the formulas and tables were transcribed using latex format. This dataset can be used for tasks such as intelligent exam paper marking and homework tutoring. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

This dataset contains 1 million Chinese programming questions with corresponding answers, detailed parses (explanations), and programming language labels. It includes a wide range of questions in C, C++, Python, Java, and JavaScript, making it ideal for training large language models (LLMs) on multilingual code understanding and generation. The questions cover fundamental to advanced topics, supporting AI applications such as code completion, bug fixing, and programming reasoning. This structured dataset enhances model performance in natural language programming tasks and helps reinforce code logic skills in AI systems. All data complies with international privacy regulations including GDPR, CCPA, and PIPL.

50,000 Sets - Image Editing Data. The editing types include human attribute editing, image semantic editing, and image structure editing. The editing targets cover scenes such as people, animals, goods, plants, and landscapes. In terms of annotation, based on the editing instructions, the targets that need to be edited in the image are edited. The data can be used for tasks such as image synthesis, data augmentation, and virtual scene generation.

This dataset includes 120,000 multimodal question-answer pairs across six major academic disciplines, including medicine, engineering, art, science, and more. Each QA pair combines textual and visual content—such as charts, diagrams, blueprints, and artworks—crafted to test logical reasoning, cross-modal understanding, and domain-specific knowledge. All questions have been reviewed by subject-matter experts to ensure academic quality and accuracy. Ideal for training multimodal large language models (MLLMs), visual question answering (VQA) systems, and AI applications requiring deep contextual reasoning, this dataset supports fine-tuning tasks like knowledge grounding, visual-text alignment, and decision-making. All data complies with GDPR, CCPA, and PIPL regulations, ensuring ethical use and privacy protection.