LAION-5B is a large-scale open dataset for training next-generation image-text models, containing 5.85 billion CLIP-filtered image-text pairs, of which 2.32 billion are in English. The dataset was created by filtering Common Crawl data using an existing CLIP model, resulting in three subsets: 2.32 billion English pairs, 2.26 billion multilingual pairs, and 1.27 billion pairs with undetectable language. The dataset includes metadata, NSFW detection scores, and a web interface for exploration. The authors demonstrate the effectiveness of LAION-5B in training models like CLIP, GLIDE, and Stable Diffusion, and show that models trained on LAION-5B perform competitively with those trained on OpenAI's original dataset. The dataset also includes tools for data curation and exploration, and the authors emphasize the importance of responsible use, cautioning against deployment in production systems without thorough evaluation. The paper discusses the technical limitations of LAION-5B, including potential biases and the challenges of large-scale data collection. It also highlights the importance of safety and ethical considerations in the use of large-scale image-text datasets. The authors advocate for open and transparent research practices, and encourage the community to contribute to the improvement of the dataset and its associated tools.LAION-5B is a large-scale open dataset for training next-generation image-text models, containing 5.85 billion CLIP-filtered image-text pairs, of which 2.32 billion are in English. The dataset was created by filtering Common Crawl data using an existing CLIP model, resulting in three subsets: 2.32 billion English pairs, 2.26 billion multilingual pairs, and 1.27 billion pairs with undetectable language. The dataset includes metadata, NSFW detection scores, and a web interface for exploration. The authors demonstrate the effectiveness of LAION-5B in training models like CLIP, GLIDE, and Stable Diffusion, and show that models trained on LAION-5B perform competitively with those trained on OpenAI's original dataset. The dataset also includes tools for data curation and exploration, and the authors emphasize the importance of responsible use, cautioning against deployment in production systems without thorough evaluation. The paper discusses the technical limitations of LAION-5B, including potential biases and the challenges of large-scale data collection. It also highlights the importance of safety and ethical considerations in the use of large-scale image-text datasets. The authors advocate for open and transparent research practices, and encourage the community to contribute to the improvement of the dataset and its associated tools.