MODEL PROFILE

LightOnOCR-3-4B-GGUF

prithivMLmods · LightOnOCR-3-4B-GGUF

> **LightOnOCR-3-4B**, developed by lightonai, is the largest and most accurate model in the LightOnOCR-3 family of end-to-end OCR vision-language models, built on the Qwen3.5-4B architecture and released under the Apache 2.0 license. Recommended for most OCR tasks, it serves as a powerful, single-model alternative to complex document understanding pipelines by combining high-quality text transcription (triggered by an empty prompt) with advanced visual understanding features. When used with the `grounding` prompt, the model outputs labeled bounding boxes for all document elements, generates short descriptions for images, and extracts numerical data from charts into structured HTML tables. Highly versatile and optimized for seamless integration with Transformers and vLLM, it excels at processing complex layouts—including tables, receipts, forms, multi-column documents, and math notation—and performs best when documents are preprocessed at 400 DPI with a target longest dimension of 2048px.

Visual QAlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/10/30 08:03:27
OVERVIEW

Model overview

> **LightOnOCR-3-4B**, developed by lightonai, is the largest and most accurate model in the LightOnOCR-3 family of end-to-end OCR vision-language models, built on the Qwen3.5-4B architecture and released under the Apache 2.0 license. Recommended for most OCR tasks, it serves as a powerful, single-model alternative to complex document understanding pipelines by combining high-quality text transcription (triggered by an empty prompt) with advanced visual understanding features. When used with the `grounding` prompt, the model outputs labeled bounding boxes for all document elements, generates short descriptions for images, and extracts numerical data from charts into structured HTML tables. Highly versatile and optimized for seamless integration with Transformers and vLLM, it excels at processing complex layouts—including tables, receipts, forms, multi-column documents, and math notation—and performs best when documents are preprocessed at 400 DPI with a target longest dimension of 2048px.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。