Cohere Releases Parse 5 (parse-v5.0): A 2.3B Vision Language Model That Turns Enterprise Documents Into Markdown

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Cohere has released Parse (parse-v5.0), a document parsing model aimed at high-volume enterprise ingestion. It is a 2.3B-parameter vision language model with an 8,192-token context window and a ~4.6GB footprint, built on Cohere Labs’ North-Micro-Vision-Instruct architecture. Parse takes a PDF, PPT or JPEG page as a base64-encoded data URI and returns Markdown containing text in reading order, tables rendered as HTML, lists, form key-value pairs, image descriptions and bounding box coordinates. There is no separate OCR stage in front of it. Cohere prices the Parse API at $1.50 per 1,000 pages and positions the model on price-performance rather than peak accuracy — a claim the company supports with a self-reported ParseBench score of 79.2 that, as we detail below, measures three of that benchmark’s five dimensions.

Is it deployable?

Yes, in production. Parse is generally available through the Cohere Parse API, Microsoft Foundry, AWS SageMaker, and single-tenant Model Vault. There is no waitlist and no research license.

Which companies: Mid-market teams that already run a RAG stack can start on metered API calls with a free trial key. Large enterprises with residency or air-gap requirements go straight to Model Vault or private deployment. Seed-stage startups can use it, but the economics only start to matter above roughly 100K pages a month.

Which industries: Cohere targets financial services, insurance, healthcare and life sciences, public sector, telecom, energy and manufacturing — the document-heavy verticals where scanned forms and dense tables are the …

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