Datalab LIFT: How a 9B Schema-First Document Extractor Stacks Up Against NuExtract3, LlamaExtract, Marker, and Docling

Datalab has released a detailed benchmark comparing its LIFT model — a 9B parameter schema-first document extraction model — against leading extractors including NuExtract3, LlamaExtract, Marker, and Docling across structured data extraction tasks. Schema-first extraction means the model is conditioned on a target output schema before processing a document, which typically yields higher precision on structured fields compared to general-purpose LLM extraction pipelines. For developers building document processing pipelines — particularly in finance, legal, or enterprise data ingestion — this benchmark provides a direct apples-to-apples comparison at the task level rather than generic NLP benchmarks. A 9B model that outperforms larger or more complex pipelines on extraction tasks would have strong practical value for teams needing to run inference on-premise or at reduced cost. Developers evaluating document extraction tooling should use this comparison as a starting checklist before committing to a pipeline architecture.