Sold by: Upstage
Deployed on AWS
Extract tables and figures from any document
Overview
Upstage Document Parse is a powerful API designed to automatically convert any document to HTML. It detects layout elements such as paragraphs, tables, images, equations, charts and more to determine the structure of the document. The API then serializes the elements according to reading order, and finally converts the document into HTML.
Highlights
- ### Key Features **Text Recognition** detects text via OCR or PDF parsing, excelling in English and CJK documents, including digital-born PDFs. **Layout Element Detection (LED)** identifies paragraphs, figures, tables, and captions, arranging them in human reading order - great for complex layouts. **Table Structure Recognition (TSR)** converts complex tables to HTML, handling merged cells and hidden gridlines.
- ### Key Applications The Upstage Document Parse model enhances LLM-based document processing and information retrieval by preserving contextual information better than traditional OCR. It is valuable for scenarios where LLMs process documents, integrating RAG with Layout Analysis via embedding techniques. It excels in information extraction and recognizing document structures across various templates, making it ideal for handling the same type of documents in different formats.
- ### Key Tasks - Document OCR - Document Parsing - Layout Analysis - Information Extraction - Layout Element Detection - Table Structure Recognition
Details
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Pricing
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Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.12xlarge Inference (Batch) Recommended | Model inference on the ml.m5.12xlarge instance type, batch mode | $15.00 |
ml.g6.2xlarge Inference (Real-Time) Recommended | Model inference on the ml.g6.2xlarge instance type, real-time mode | $15.00 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $15.00 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $15.00 |
ml.g5.2xlarge Inference (Real-Time) | Model inference on the ml.g5.2xlarge instance type, real-time mode | $15.00 |
ml.g4dn.xlarge Inference (Real-Time) | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $15.00 |
ml.g6.xlarge Inference (Real-Time) | Model inference on the ml.g6.xlarge instance type, real-time mode | $15.00 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
❗ Important Notice It requires NVIDIA Driver version 525.0 or later and is optimized for ml.g6 instances. For users running ml.g5 instances, please use version 251217-cu121 for compatibility.
🚀 Updates
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Updated hwp conversion module license. hwp support will be unavailable after December 31, 2025 on versions earlier than 251217.1.
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Improved recognition performance through additional training on a Japanese handwritten dataset
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Fixed an issue where all word-level confidence scores were returned as 0.0
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Fixed a deadlock issue where the process could hang when model inference failed
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Enhanced resilience to CUDA OOM errors caused by memory fragmentation during service deployment
Additional details
Inputs
- Summary
Provide input data in multipart form data View more detailed description here
- Input MIME type
- multipart/form-data
https://console.upstage.ai/_next/image?url=%2Fassets%2Fimages%2Fdocs%2Finvoice.png&w=1920&q=75
BATCH INFERENCE IS NOT SUPPORTED NOW
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