Parse

Skip to content The state of sovereign AI adoption: What enterprise leaders need to know. Read now

Products

Solutions

Resources

Blog

Research

Company

Sign in

Request a demo

Platform North

Enterprise-ready AI for business

Compass

Intelligent search and discovery

Models Command

Generative language models

Transcribe New

Speech recognition model

North Mini Code

Agentic coding model

Parse New

Document parsing model

Embed

Search and discovery model

Rerank

Semantic search ranking

Models Overview

Product Products Overview

Total Cost of AI Ownership

Pricing

Featured Command: High-performance generative AI models for real-world applications

Deploy Model Vault

Dedicated model inference platform

Private Deployments

On-prem or isolated VPCs

Security

Protect your data at every stage

See deployment options

By Industry Financial Services

Public Sector

Technology

Telecommunications

Energy and Utilities

Healthcare and Life Sciences

Manufacturing

Featured Model Vault provides fully-isolated, performant inference with Saas simplicity

Insights Customer Stories

For Developers Developers

Models Overview

Docs

Discord

LLM University

Connect Partners

Events

Webinars

Merch Store

Featured How CoreWeave used Cohere North to transform its customer support in 90 days

Blog

The latest news, launches, and insights

Read more

The state of sovereign AI adoption in 2026

Cohere and the University of Waterloo launch partnership to strengthen Canada’s AI talent pipeline

Introducing North Automations: Intelligent workflow orchestration

Research Cohere Labs

Cohere’s ML research lab

Explorations Future(s) of Work

How will AI change the way we work?

Aya Models

Multilingual AI at scale

All Papers

Initiatives Research Scholars

Finding the new generation of ML talent

Open Science Community

Championing global, open science

Catalyst Grants

Supporting impactful ML endeavors

Resources Blog

Hugging Face

Events

Featured The future of work debate has an evidence problem

About

Careers

Newsroom

Aug 27, 2026

5 minute read

Introducing Parse: Enterprise document intelligence at scale A high-throughput vision parsing model with the strongest price-performance profile on the market.

Key takeaways Best-in-class value : outperforms leading document parsers and hyperscaler services while remaining cost-effective at enterprise scale. Beyond OCR : understands tables, forms, diagrams, and images to extract richer semantic context across key global commercial languages. Enterprise-first : trained to handle business documents in major industries and domains, such as finance, insurance, and scientific work. Spatially aware : returns bounding boxes for visual elements, preserving document structure for retrieval, grounding, and automation. Available in Compass : use Parse today as part of Cohere’s Compass search and retrieval stack - alongside Embed, and Rerank. Secure deployments : run in any private cloud or on-premises environment to match your organization's security and compliance profile.

Cohere Parse is a cost-effective vision language model for processing large volumes of enterprise documents. It converts complex, multimodal files into structured, machine-readable data that can power enterprise knowledge use cases–including document indexing, RAG, and agentic retrieval.

More than text recognition, Parse detects and understands key visual elements - such as tables and embedded images - and returns clean Markdown files for downstream processing and application. Use Parse to process your documents and images across nine major world languages.

Parse is designed to preserve parsing quality and keep inference costs predictable as workloads scale. It supports the high-throughput needed in production environments. Customers can access Parse through the Cohere API for just $1.50 per 1,000 pages, or deploy in Model Vault for secure, single-tenant inference and even further cost savings per page. Teams in regulated industries can deploy Parse securely on their own infrastructure with a minimal serving footprint.

Want to try it first? See how Cohere Parse handles your documents for free using our Space . Performance Cohere Parse delivers the strongest price–performance tradeoff among the models we evaluated. It is a highly competitive model that outperforms leading specialized document parsing solutions while maintaining a price point suitable for high-volume workloads spanning hundreds of thousands to millions of pages. Pareto frontier of performance (ParseBench three-dimension average) versus price (USD per 1,000 pages) across the evaluated models. Price is shown on a logarithmic scale to account for the wide range included. On ParseBench - which measures agent-suitable parsing performance - Parse scores 79.2 across three evaluation dimensions compared with 74.5 for Mistral OCR 4, 72.4 for Databricks AI Parse, and 78.3 for LlamaParse’s Cost Effective offering.

This performance gap is even larger compared with hyperscaler document intelligence solutions, with an over 20-point improvement on both AWS Textract and Google Document AI. In our evaluation set, Parse is only bettered by the frontier LLMs (GPT-5.5, Opus 4.8 and Gemini 3.5 Flash) - each general purpose and significantly larger than Parse. ParseBench average scores over three capability dimensions for a representative set of proprietary and open-weight document parsing and OCR tools.

Model Average Tables Content Faithfulness Semantic Formatting

Cohere Parse 79.2 87.0 86.6 64.0

GPT-5.5 84.4 89.3 87.5 76.5

Opus 4.8 84.3 89.7 89.0 74.1

Gemini 3.5 Flash 81.8 87.6 84.7 73.2

LlamaParse (Cost Effective) 78.3 81.4 90.9 62.7

Chandra OCR 2 (open) 77.7 89.2 83.7 60.3

Mistral OCR 4 74.5 73.9 89.5 60.1

Databricks AI Parse 72.4 83.7 88.3 45.3

Azure Document Intelligence 69.3 86.0 84.9 37.0

Deepseek-OCR 2 (open) 65.9 61.7 82.0 54.0

dots.mocr (open) 63.2 85.2 89.5 14.9

Google Document AI 57.3 55.1 83.7 33.0

AWS Textract 53.3 82.3 74.8 2.8

ParseBench scores by capability dimension. Tables tests for accurate structural extraction of data grids and cells. Content Faithfulness tests for text omissions, hallucinations, and broken reading order. Semantic Formatting 1 measures a model’s ability to capture styles that change data meaning, such as strike-throughs or italics. This evaluation did not test for Charts or Visual Grounding 2 . (Zhang et al. , 2026)

In terms of throughput, Cohere Parse processes 4.5...