{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/essential-web-v1-0-24t-tokens-of-organized","title":"Essential-Web v1.0: 24T tokens of organized web data","arxiv_id":"2506.14111","date":"2025-06-17","proceeding":null,"authors":["Essential AI",":","Andrew Hojel","Michael Pust","Tim Romanski","Yash Vanjani","Ritvik Kapila","Mohit Parmar","Adarsh Chaluvaraju","Alok Tripathy","Anil Thomas","Ashish Tanwer","Darsh J Shah","Ishaan Shah","Karl Stratos","Khoi Nguyen","Kurt Smith","Michael Callahan","Peter Rushton","Philip Monk","Platon Mazarakis","Saad Jamal","Saurabh Srivastava","Somanshu Singla","Ashish Vaswani"],"abstract":"Data plays the most prominent role in how language models acquire skills and knowledge. The lack of massive, well-organized pre-training datasets results in costly and inaccessible data pipelines. We present Essential-Web v1.0, a 24-trillion-token dataset in which every document is annotated with a twelve-category taxonomy covering topic, format, content complexity, and quality. Taxonomy labels are produced by EAI-Distill-0.5b, a fine-tuned 0.5b-parameter model that achieves an annotator agreement within 3% of Qwen2.5-32B-Instruct. With nothing more than SQL-style filters, we obtain competitive web-curated datasets in math (-8.0% relative to SOTA), web code (+14.3%), STEM (+24.5%) and medical (+8.6%). Essential-Web v1.0 is available on HuggingFace: https://huggingface.co/datasets/EssentialAI/essential-web-v1.0","url_abs":"https://arxiv.org/abs/2506.14111v2","url_pdf":"https://arxiv.org/pdf/2506.14111v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"essential-web-v1-0-24t-tokens-of-organized","repo_url":"https://github.com/essential-ai/eai-taxonomy","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"math","task_name":"Math"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2506.14111","atlas_url":"https://app.syntology.ai/?focus=2506.14111","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}