Cohere Launches Parse 5: A 2.3B Vision-Language Model for Enterprise Document Extraction

Cohere has released Parse 5 (parse-v5.0), a 2.3 billion parameter vision-language model purpose-built for converting enterprise documents — including PDFs, scanned forms, and complex layouts — into structured Markdown output. The relatively compact model size is notable: at 2.3B parameters, Parse 5 is designed for efficient deployment in enterprise environments where running large multimodal models at scale carries prohibitive cost. Document-to-Markdown conversion is a foundational step in many RAG and agentic pipelines, and a specialized model outperforming general-purpose alternatives at this task would have meaningful downstream impact on extraction quality. Developers building document ingestion pipelines should evaluate Parse 5 against current approaches using GPT-4o or Claude for document parsing, particularly for high-volume or cost-sensitive workflows. Cohere's positioning of Parse 5 as an enterprise-grade tool also suggests it will come with the data privacy and deployment flexibility commitments that regulated industries require.