ExactRead

Model guide

OCR Model Comparison — Compare Format, Cost, and Output

OCR model comparison on ExactRead: run vision models and native OCR engines on the same document, weigh accuracy, cost, and file support, then standardize on the best fit.

Open workbenchView pricing

Pick an OCR model

Each model has its own page to test it and review capability, format support, credits, and release date.

olmOCR 2New
Allen Institute for AI · Oct 2025
Native OCR engineImages and PDF1 cr
Qwen3-VL 32BNew
Alibaba Qwen · Sep 2025
Vision-language modelImage files2 cr
Qwen3-VL 8BNew
Alibaba Qwen · Sep 2025
Vision-language modelImage files1 cr
PaddleOCR-VL 1.6
Baidu PaddlePaddle · May 2025
Native OCR engineImages and PDF1 cr
GPT-4.1
OpenAI · Apr 2025
Vision-language modelImage files3 cr
GPT-4.1 mini
OpenAI · Apr 2025
Vision-language modelImage files1 cr
Gemini 2.5 Flash
Google · Apr 2025
Vision-language modelImage files1 cr
Mistral OCR
Mistral AI · Mar 2025
Native OCR engineImages and PDF2 cr
Gemini 2.5 Pro
Google · Mar 2025
Vision-language modelImage files3 cr
Qwen2.5-VL 32B
Alibaba Qwen · Mar 2025
Vision-language modelImage files1 cr
OLMOCR
Allen Institute for AI · Feb 2025
Native OCR engineImages and PDF1 cr
Gemini 2.0 Flash
Google · Feb 2025
Vision-language modelImage files1 cr
Qwen2.5-VL 72B
Alibaba Qwen · Jan 2025
Vision-language modelImage files2 cr
MinerU
OpenDataLab · Aug 2024
Native OCR engineImages and PDF1 cr
Qwen-VL Max
Alibaba DashScope · Aug 2024
Vision-language modelImage files2 cr
GPT-4o mini
OpenAI · Jul 2024
Vision-language modelImage files1 cr
Datalab OCR
Datalab · Jun 2024
Native OCR engineImages and PDF1 cr
Datalab Marker
Datalab · Jun 2024
Native OCR engineImages and PDF1 cr
GPT-4o
OpenAI · May 2024
Vision-language modelImage files2 cr
Azure Document Intelligence
Microsoft Azure · Jul 2023
Native OCR engineImages and PDF2 cr
PaddleOCR
Baidu PaddlePaddle · Jan 2023
Native OCR engineImages and PDF1 cr
Mathpix OCR
Mathpix · Jan 2023
Native OCR engineImage files2 cr
AWS Textract
AWS · May 2019
Native OCR engineImages and PDF2 cr
Google Cloud Vision OCR
Google · Dec 2017
Native OCR engineImages and PDF2 cr
Gemini 3 Flash
Google
Vision-language modelImage files1 cr
Gemini 3.1 Pro
Google
Vision-language modelImage files3 cr
GPT-5.4 mini
OpenAI
Vision-language modelImage files1 cr
GPT-5.4
OpenAI
Vision-language modelImage files3 cr

Mix every model in one dashboard

Upload once, compare multiple OCR models side by side, accept the best, and export TXT or JSON.

Open the multi-model dashboard

OCR model comparison on your documents

The best OCR model comparison is not a leaderboard — it is your own document read by several engines at once. ExactRead lists 20+ models, from vision-language models like GPT-5.4, Gemini 3 Flash, and Qwen3-VL to native OCR engines like Mistral OCR, PaddleOCR, AWS Textract, and Google Cloud Vision, and lets you run any of them on the same file. Reading the outputs side by side turns an OCR accuracy comparison into something you can actually verify instead of guess.

Model choice changes with the document

A model that nails receipts may struggle with cursive handwriting or dense multi-column PDFs. Native OCR engines are predictable on printed text and structured forms; vision-language models are more flexible on messy layouts and mixed languages but can paraphrase. An OCR model comparison keeps those tradeoffs visible so you standardize on the engine that fits your real documents, not a headline benchmark.

Weigh accuracy against cost and speed

Every model carries a per-document credit cost and a speed profile. A cheap, fast model may be right for high-volume routine reading, while a higher-cost model earns its keep on rare, high-value pages. The catalog shows type, format support, and credits per model, so an OCR accuracy comparison can be balanced against what each run actually costs.

Let your documents decide

The catalog and this table are only a starting point. Upload a representative sample, run three or four models in compare mode, and let the results — not the spec sheet — pick the engine. Save the winner as a preference, then switch to a single model to keep credit use low once you have standardized.

Current-generation vs legacy models

The catalog marks older models as legacy — they still route and run, and they keep existing jobs and preferences working, but automatic model selection favors current-generation engines like Gemini 3 Flash, GPT-5.4, and Qwen3-VL. For a fresh OCR model comparison, start from the current generation and only reach for a legacy model when a specific document reads better on it. Each entry lists its release date so you can see how recent a model is at a glance.

How it works

  1. 1

    Upload your document

    Drop a document onto the workbench or click to browse. Supported inputs are PNG, JPEG, and WebP images, plus PDF for PDF-capable models.

  2. 2

    Let ExactRead filter the models

    After upload, the model list is filtered to the OCR engines that actually support your file, so you never start a job that cannot run.

  3. 3

    Run one model or compare several

    Choose a single model when speed and cost matter, or compare mode to run several OCR models on the same document at once.

  4. 4

    Review confidence and warnings

    Each result keeps its model, status, confidence, and warnings, with the recommended output highlighted so you can judge accuracy quickly.

  5. 5

    Accept and export TXT or JSON

    Accept the output that reads your document most faithfully, then copy it or export TXT or JSON for the next step.

Models that suit this document type

Capability, format support, and credits come straight from the model catalog — a starting point, not a ranking. Test on your own documents to decide.

ModelProviderTypeFormatsCredits / doc
Gemini 3 FlashGoogleVision-language modelImage files1
GPT-5.4OpenAIVision-language modelImage files3
Mistral OCRMistral AINative OCR engineImages and PDF2
PaddleOCRBaidu PaddlePaddleNative OCR engineImages and PDF1
Qwen3-VL 32BAlibaba QwenVision-language modelImage files2

Supported formats

Image and PDF support is listed per model

Model guidance

Use the catalog to compare cost, capability, and file support

Credit note

Admins configure the catalog and per-model credits

Back to ExactRead homeView OCR credit pricing

Frequently asked questions

Which models can ExactRead use?

The catalog includes 20+ vision models and native OCR engines — GPT-5.4, Gemini 3 Flash, Qwen3-VL, Mistral OCR, PaddleOCR, AWS Textract, Azure Document Intelligence, Google Cloud Vision, olmOCR, MinerU, and more. Browse the model directory for the full list.

How do I run an OCR accuracy comparison?

Upload one representative document, switch to compare mode, select two to four models, and run. ExactRead shows the outputs side by side with confidence and warnings so you can judge accuracy on your own file.

Is there a single most accurate OCR model?

No. Accuracy depends on your document type, language, and image quality. That is why ExactRead focuses on OCR model comparison on your files rather than publishing a single ranking.

Can I disable expensive models?

Yes. Admin settings control the OCR catalog and the per-model credit costs, so you can hide models you do not want or adjust their credit price.

What does an OCR model comparison cost?

Compare mode charges each selected model its per-document credits, so a four-model run costs the sum of those four. The free plan's 100 monthly credits cover several comparison runs.