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PaddleOCR-VL-1.6

by PaddlePaddle PaddlePaddle/PaddleOCR-VL-1.6

PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training We introduce PaddleOCR-VL-1.6, an upgraded compact document parsing model built upon PaddleOCR-VL-1.5.

Parameters959M
Context131,072
Weights1.9 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads35.7k

Runs On

What it takes to serve PaddleOCR-VL-1.6 (959M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 1.9 GB 2.3 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 1.0 GB 1.2 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.5 GB 0.6 GB 1x MI300X (192 GB)
Vultr		 $1.85 1x H100 $1.99 · 1x MI325X $2.00

Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Sep 18, 2026.

Model Card

By PaddlePaddle, published under apache-2.0, revision c5630abae1d9.

PaddleOCR-VL-1.6: Expanding the Frontier of Document Parsing with Under-Optimized Region Refinement and Progressive Post-Training

[![repo](https://img.shields.io/github/stars/PaddlePaddle/PaddleOCR?color=ccf)](https://github.com/PaddlePaddle/PaddleOCR) [![HuggingFace](https://img.shields.io/badge/HuggingFace-black.svg?logo=data:image/png;base64,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&labelColor=white)](https://huggingface.co/PaddlePaddle/PaddleOCR-VL-1.6) [![ModelScope](https://img.shields.io/badge/ModelScope-black?logo=data:image/svg+xml;base64,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&labelColor=white)](https://modelscope.cn/models/PaddlePaddle/PaddleOCR-VL-1.6) [![HuggingFace](https://img.shields.io/badge/Demo_on_HuggingFace-black.svg?logo=data:image/png;base64,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&labelColor=white)](https://huggingface.co/spaces/PaddlePaddle/PaddleOCR-VL-1.6_Online_Demo) [![ModelScope](https://img.shields.io/badge/Demo_on_ModelScope-black?logo=data:image/svg+xml;base64,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&labelColor=white)](https://modelscope.cn/studios/PaddlePaddle/PaddleOCR-VL-1.6_Online_Demo/summary) [![Discord](https://img.shields.io/badge/Discord-ERNIE-5865F2?logo=discord&logoColor=white)](https://discord.gg/JPmZXDsEEK) [![X](https://img.shields.io/badge/X-PaddlePaddle-6080F0)](https://x.com/PaddlePaddle) [![License](https://img.shields.io/badge/license-Apache_2.0-green)](./LICENSE) ** [Official Website](https://www.paddleocr.com)** ** [Technical Report](https://arxiv.org/pdf/2606.03264)**

Introduction

We introduce PaddleOCR-VL-1.6, an upgraded compact document parsing model built upon PaddleOCR-VL-1.5. PaddleOCR-VL-1.6 introduces a region-aware data optimization framework that identifies weak regions from the previous model, applies targeted enhancement to those regions, and improves the reliability of supervision signals. It further adopts a progressive post-training recipe based on curated data selection and reinforcement learning, pushing model performance to a higher level through staged optimization. PaddleOCR-VL-1.6 achieves a new state-of-the-art score of 96.33% on OmniDocBench v1.6, sets new records on OmniDocBench v1.5 and Real5-OmniDocBench as well, and demonstrates strong competitiveness against top-tier VLMs. The model architecture is fully compatible with PaddleOCR-VL-1.5, enabling zero-cost plug-and-play migration.

Key Capabilities of PaddleOCR-VL-1.6

Read the full model card (1,031 words)

Configuration

Architecture
PaddleOCRVLForConditionalGeneration
Context length (tokens)
131,072
Layers
18
Hidden size
1,024
Feed-forward size
3,072
Attention heads
16
Key/value heads
2
Head dimension
128
Vocabulary size
103,424
RoPE base
500,000
Stored precision
bfloat16
Model type
paddleocr_vl

Identity and Version

Repository
PaddlePaddle/PaddleOCR-VL-1.6
Publisher
PaddlePaddle
Task
Image and text to text
Modality
Image and text
Library
PaddleOCR
Parameters
959M parameters
Languages
en, zh
Revision
c5630abae1d940eafe0697512a0325494b02ab42
First published
2026-05-27
Last updated
2026-08-08

Files and Weights

20 files, 1.9 GB in total. The weights are 1 file totalling 1.9 GB in safetensors.

Weights1 file · 1.9 GB
Configuration12 files · 180.2 KB
Tokenizer3 files · 13.0 MB
Documentation2 files · 32.8 KB
Other1 file · 1.5 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights1.9 GB 85a479d506a1
.eval_results/real5_omnidocbench.yamlConfiguration1.4 KB —
added_tokens.jsonConfiguration25.4 KB —
config.jsonConfiguration2.1 KB —
configuration_paddleocr_vl.pyConfiguration8.1 KB —
generation_config.jsonConfiguration133 B —
image_processing_paddleocr_vl.pyConfiguration25.0 KB —
inference.ymlConfiguration43 B —
modeling_paddleocr_vl.pyConfiguration103.9 KB —
preprocessor_config.jsonConfiguration641 B —
processing_paddleocr_vl.pyConfiguration12.3 KB —
processor_config.jsonConfiguration137 B —
special_tokens_map.jsonConfiguration1.2 KB —
LICENSEDocumentation11.4 KB —
README.mdDocumentation21.4 KB —
chat_template.jinjaOther1.5 KB —
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer11.2 MB c8a215a59183
tokenizer.modelTokenizer1.6 MB 34ef7db83df7
tokenizer_config.jsonTokenizer186.9 KB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
1.9 GB
Download from PaddlePaddle

Released by PaddlePaddle through its official repository on Hugging Face. Read the license.

Built From

  • Described by arXiv:2606.03264

Evaluations

Each result is shown as reported, with the conditions its reporter stated. None is a SAVRN measurement. A comparison lines two results up only when their configuration, unit and setup are all stated and identical.

BenchmarkConditionsResultReported byRevisionDate
Delores-Lin/MDPBench Task arMetric arComparison conditions not established 76.2 MDPBench leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-15
Delores-Lin/MDPBench Task deMetric deComparison conditions not established 85.1 MDPBench leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-15
Delores-Lin/MDPBench Task digitalMetric digitalComparison conditions not established 87.1 MDPBench leaderboard
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Delores-Lin/MDPBench Task enMetric enComparison conditions not established 83.5 MDPBench leaderboard
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Delores-Lin/MDPBench Task esMetric esComparison conditions not established 75.1 MDPBench leaderboard
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Delores-Lin/MDPBench Task frMetric frComparison conditions not established 78.6 MDPBench leaderboard
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Delores-Lin/MDPBench Task hiMetric hiComparison conditions not established 70.7 MDPBench leaderboard
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Delores-Lin/MDPBench Task idMetric idComparison conditions not established 82.7 MDPBench leaderboard
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Delores-Lin/MDPBench Task itMetric itComparison conditions not established 85.5 MDPBench leaderboard
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Delores-Lin/MDPBench Task jpMetric jpComparison conditions not established 70.3 MDPBench leaderboard
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Delores-Lin/MDPBench Task koMetric koComparison conditions not established 86.3 MDPBench leaderboard
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Delores-Lin/MDPBench Task latinMetric latinComparison conditions not established 81.4 MDPBench leaderboard
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Delores-Lin/MDPBench Task nlMetric nlComparison conditions not established 80.5 MDPBench leaderboard
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Delores-Lin/MDPBench Task non_latinMetric non_latinComparison conditions not established 76.1 MDPBench leaderboard
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Delores-Lin/MDPBench Task overallMetric overallComparison conditions not established 78.9 MDPBench leaderboard
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Delores-Lin/MDPBench Task photographedMetric photographedComparison conditions not established 76.3 MDPBench leaderboard
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Delores-Lin/MDPBench Task privateMetric privateComparison conditions not established 83 MDPBench leaderboard
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Delores-Lin/MDPBench Task ptMetric ptComparison conditions not established 80.9 MDPBench leaderboard
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Delores-Lin/MDPBench Task thMetric thComparison conditions not established 67.3 MDPBench leaderboard
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Delores-Lin/MDPBench Task zhMetric zhComparison conditions not established 85.9 MDPBench leaderboard
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Delores-Lin/MDPBench Task zh_tMetric zh_tComparison conditions not established 76.7 MDPBench leaderboard
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PaddlePaddle/Real5-OmniDocBench Task illuminationMetric illuminationComparison conditions not established 93.28 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
PaddlePaddle/Real5-OmniDocBench Task overallMetric overallComparison conditions not established 93.19 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
PaddlePaddle/Real5-OmniDocBench Task scanningMetric scanningComparison conditions not established 94.74 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
PaddlePaddle/Real5-OmniDocBench Task screen_photographyMetric screen_photographyComparison conditions not established 92.78 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
PaddlePaddle/Real5-OmniDocBench Task skewMetric skewComparison conditions not established 92.66 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
PaddlePaddle/Real5-OmniDocBench Task warpingMetric warpingComparison conditions not established 92.48 Real5-OmniDocBench Leaderboard
Reported by a third party		 Evaluated revision not stated 2026-08-08
allenai/olmOCR-bench Task old_scansMetric old_scansSetup PaddleOCR-VL-1.6 pipeline, greedy, no tuning; old_scans.jsonl sub-scoreComparison conditions not established 38.6 ocr-bench — old_scans eval
Reported by a third party		 Evaluated revision not stated 2026-06-27
llamaindex/ParseBench Task chartMetric chartSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 54.24 ParseBench
Reported by a third party		 Evaluated revision not stated 2026-06-01
llamaindex/ParseBench Task layoutMetric layoutSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 77.8 ParseBench
Reported by a third party		 Evaluated revision not stated 2026-06-01
llamaindex/ParseBench Task meanMetric meanSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 67.43 ParseBench
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llamaindex/ParseBench Task tableMetric tableSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 67.77 ParseBench
Reported by a third party		 Evaluated revision not stated 2026-06-01
llamaindex/ParseBench Task text_contentMetric text_contentSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 82.71 ParseBench
Reported by a third party		 Evaluated revision not stated 2026-06-01
llamaindex/ParseBench Task text_formattingMetric text_formattingSetup Pipeline name: paddleocr_vl_1_6_pipelineComparison conditions not established 54.64 ParseBench
Reported by a third party		 Evaluated revision not stated 2026-06-01

Memory Requirements

PrecisionWeights in memory
As published1.9 GB
16-bit1.9 GB
8-bit1.0 GB
4-bit0.5 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Compare PaddleOCR-VL-1.6

Questions About PaddleOCR-VL-1.6

How much GPU memory does PaddleOCR-VL-1.6 need?

About 2.3 GB at 16-bit and 0.6 GB at 4-bit: the weights (959M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run PaddleOCR-VL-1.6 on?

At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.

Can I use PaddleOCR-VL-1.6 commercially?

Yes. PaddleOCR-VL-1.6 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is PaddleOCR-VL-1.6's context length?

131,072 tokens, from the maximum position embeddings in its published configuration.

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