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Cohere Releases Parse 5, a 2.3B Vision Language Model for Enterprise Document Parsing

Cohere has launched Parse 5, a 2.3B vision language model that converts documents to Markdown, priced at $1.50 per 1,000 pages.

AI News Feed · 2026-08-28 09:06

Built on Cohere Labs' North-Micro-Vision-Instruct architecture, the model has an 8,192-token context window and a footprint of about 4.6GB. It accepts a page as a base64-encoded data URI and returns Markdown containing text in reading order, HTML tables, lists, form key-value pairs, image descriptions, and bounding box coordinates. There is no separate OCR stage in front of it, and it recovers text, tables, layouts, and page boundaries in one pass. Nine languages are listed as stable: Arabic, English, French, German, Italian, Japanese, Korean, Portuguese, and Spanish, with zero-shot support elsewhere at lower accuracy.

Cohere says the model is generally available through the Cohere Parse API, Microsoft Foundry, AWS SageMaker, and single-tenant Model Vault, with no waitlist or research license. Mid-market teams running a RAG stack can start with a free trial key on metered API calls, while large enterprises with residency or air-gap requirements can use Model Vault or private deployment. The API costs $1.50 per 1,000 pages. Model Vault costs $4 per hour or $2,500 per month for a Medium instance and $7 per hour or $4,300 per month for XL. As MarkTechPost notes, a Medium instance breaks even against metered pricing at roughly 1.67 million pages per month, and XL at about 2.87 million; below those volumes, metered calls are cheaper.

Target industries include financial services, insurance, healthcare, life sciences, public sector, telecom, energy, and manufacturing. Applications include RAG ingestion, intelligent document processing, claims and invoice pipelines, contract and filing search, and providing document context to agents. An output mode called blocks returns typed blocks with HTML tables, bounding boxes, and descriptions, enabling citation-level traceability.

On accuracy, Cohere reports a ParseBench score of 79.2, averaging across three of the benchmark's five dimensions: tables, content faithfulness, and semantic formatting, while dropping charts and visual grounding. MarkTechPost points out that this is a vendor-reported subset score, not a leaderboard position, and that Cohere's model is not currently listed on the public leaderboard, where LlamaParse Agentic leads at 84.88. The same report says other vendors score far lower on the full five-dimension overall: Mistral OCR 4 and Databricks AI Parse at 60.68, and Azure Document Intelligence at 59.64.