LLM training data

LLM training data is text licensed for pre-training, fine-tuning and evaluating language models: books, articles, technical documents, transcripts, forum discussions, code, multilingual corpora, and instruction or preference data written by people. AI labs and enterprise teams buy it to improve performance in specific domains, languages and tasks, and to replace content of uncertain provenance with licensed sources.

Typical fields

• Document ID and source or publisher
• Text content with character or token counts
• Language and script
• Domain or topic labels
• Publication or creation date
• Licence and rights metadata per document
• Quality, toxicity and deduplication flags
• For instruction data: prompt, response, rating and annotator metadata

Sources and methods

Licensed corpora come from publishers, archives, platforms with user consent and commissioned writing. Instruction and preference datasets are produced by trained annotators following written guidelines. Providers clean text, remove boilerplate, deduplicate near-identical documents, filter personal data and toxic content and attach rights metadata. In the EU, rights holders can opt out of commercial text and data mining, so provenance and opt-out checks matter.

Delivery and pricing

Data is delivered as JSON Lines or Parquet in cloud storage. Pricing is often per million tokens, per document or a flat licence, with custom instruction data priced per example. Exclusivity, rare languages and specialist domains increase price.

Before you buy

• Require explicit AI training rights and a clear chain of rights.
• Ask how personal data and opt-outs were handled.
• Check deduplication against public web corpora such as Common Crawl.
• Test for overlap with your evaluation benchmarks.
• Recount tokens with the tokenizer you use.