What are the hardware requirements for Surya Ocr 2?

Surya Ocr 2 requires approximately 1.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Surya Ocr 2 and how large is it?

Surya Ocr 2 is developed by datalab-to, a model with 686.2m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Surya Ocr 2?

Surya Ocr 2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Surya Ocr 2 by datalab-to — VRAM 1.4GB

Name: Surya Ocr 2
Author: datalab-to

Surya Ocr 2 is an open-source language model by datalab-to. Features: 686.2m LLM, VRAM: 1.4GB, License: openrail, LLM Explorer Score: 0.38.

Arxiv:2105.15203 Conversational Endpoints compatible Eval-results Image-text-to-text Layout Markdown Ocr Pdf Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/datalab-to/surya-ocr-2

Surya Ocr 2 Parameters and Internals

LLM Name	Surya Ocr 2
Repository 🤗	https://huggingface.co/datalab-to/surya-ocr-2
Model Size	686.2m
Required VRAM	1.4 GB
Updated	2026-08-09
Maintainer	datalab-to
Model Type	qwen3_5
Model Files	1.4 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	openrail
Transformers Version	5.2.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>

Rank the Surya Ocr 2 capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Surya Ocr 2

Model	Likes	Downloads	VRAM
Bina 0.1 Koochik FP16	0	88	1 GB