OCR Arena

Product Introduction

1. OCR Arena is a free online platform designed for comparing and evaluating the performance of leading Vision-Language Models (VLMs) and Optical Character Recognition (OCR) models through direct, side-by-side analysis. Users can upload documents, images, or PDFs to test model accuracy and contribute to a publicly ranked leaderboard.
2. The core value of OCR Arena lies in its ability to democratize model evaluation by providing transparent, crowdsourced benchmarks that help users identify the most reliable OCR/VLM tools for real-world applications.

Main Features

1. Users can upload documents in PDF, JPEG, or PNG formats to initiate anonymous OCR battles, where two randomly assigned models extract text from the same file for accuracy comparison.
2. The platform maintains a dynamic public leaderboard ranking models based on ELO scores, win rates, and total battles, with metrics updated in real time as users vote on results.
3. A "random document" feature allows users to test models on pre-selected files, ensuring standardized benchmarking across diverse document types and complexity levels.

Problems Solved

1. OCR Arena addresses the challenge of selecting optimal OCR/VLM models for specific use cases by providing empirical, user-driven performance data instead of relying on theoretical benchmarks.
2. The platform serves developers, data scientists, and enterprise teams requiring accurate text extraction from scanned documents, invoices, or handwritten notes for automation pipelines.
3. Typical scenarios include evaluating model performance on low-quality scans, multilingual documents, or complex layouts before integrating OCR tools into production systems.

Unique Advantages

1. Unlike proprietary evaluation tools, OCR Arena enables direct comparison of commercial and open-source models (e.g., Gemini, GPT-5 variants, DeepSeek OCR) in head-to-head battles with identical input conditions.
2. The ELO ranking system adapts to user voting patterns, creating a competitive environment where models gain/lose points based on battle outcomes, mirroring chess tournament scoring mechanics.
3. Competitive differentiation comes from combining anonymous model testing to eliminate brand bias, support for multi-page PDF analysis, and community-driven validation at scale without requiring API keys or subscriptions.

Frequently Asked Questions (FAQ)

1. What file formats does OCR Arena support for battles? The platform accepts PDF, JPEG, and PNG files up to 50MB, with multi-page PDF processing capabilities for testing document structure retention.
2. How does the leaderboard calculate model rankings? Models receive ELO points based on battle outcomes, with win rates calculated from user votes on text extraction accuracy across font types, layouts, and language support.
3. Can I test private or custom models on OCR Arena? The platform currently focuses on pre-integrated public models, but users can request new model integrations through the developer team at extend.ai.
4. Are battle results stored for later reference? All battles contribute anonymously to model statistics, but individual user uploads are deleted after 24 hours to ensure data privacy.
5. How frequently are new models added to the platform? The maintainers update the model roster quarterly, prioritizing models with significant GitHub activity or commercial adoption in enterprise OCR workflows.