The 7 Best Free OCR Tools in 2026 (That Don’t Upload Your Files)

OCR (optical character recognition) extracts text from images and scanned documents. The standard tools — Adobe Acrobat online, Google Drive, OCR.space — all work, but they all upload your images to a third-party server. For a receipt with your address, a screenshot of an API key, or any document you would not paste into ChatGPT, that upload is a real concern.

This post lists the best free OCR tools that keep your files local. Each was tested on a clean 1-page receipt, a 5-page scanned PDF, and a phone photo of a printed page.

The 7 best free OCR tools

1. Uttir Image to Text (OCR)

The Uttir OCR tool runs entirely in your browser. Drop an image (PNG, JPG, WebP), pick a language from 12 supported, get the text. Per-language data files are about 10 MB and cached after the first run. For a receipt or screenshot, it returns clean text in 5-10 seconds.

Best for: receipts, screenshots, photos of printed text, single-page documents.

2. Uttir PDF OCR

The Uttir PDF OCR is the same engine with PDF support. Drop a scanned PDF (image-based, not text-based), get the text out. Multi-page support, page-by-page output. Useful for old scanned books, contracts, and reports.

Best for: scanned PDFs, multi-page documents, archives.

3. Tesseract.js (Self-Hosted)

Tesseract.js is the open-source OCR engine that the browser-based tools use. You can run it in your own Node.js script, your own web page, or a Docker container. Free, no upload, no third party. The setup is non-trivial (WASM runtime, language data files, output parsing).

Best for: developers who want to integrate OCR into their own pipeline.

4. Apple Live Text (iPhone, iPad, Mac)

If you have an iPhone or modern Mac, the built-in Live Text feature does on-device OCR in Photos, the camera, and any image you open. No upload, no third party, no extra app. Tap the text icon in the bottom-right of any image to select and copy the text.

Best for: iPhone / Mac users who want zero-setup OCR for photos.

5. Google Keep (Android / Web)

Google Keep's "Grab image text" feature does OCR on photos you add to notes. The image is uploaded to Google for processing. Convenient on Android; less so for privacy-sensitive documents.

Best for: Android users who already use Google Keep and don't mind the upload.

6. Microsoft Lens (Mobile)

Microsoft Lens (formerly Office Lens) is a free mobile app that captures documents, whiteboards, and photos and extracts the text. Available on iOS and Android. Free, with optional Microsoft 365 sign-in for cloud sync.

Best for: capturing whiteboard notes or printed documents on a phone.

7. OCR.space (Free API)

OCR.space is a free OCR API with 25,000 requests/month on the free tier. The images you send are processed on their servers. Useful for integrating OCR into your own apps where you control the data flow and have a privacy policy covering the upload.

Best for: developers building OCR features into their own apps, with their own privacy disclosure.

How to choose

For one-off documents (receipts, screenshots, photos): start with the Uttir OCR tool. If you need PDF support, use the PDF OCR. Both are free, no signup, no upload.

For developers building OCR into an app: use Tesseract.js in your own code (most flexible) or OCR.space (easiest API, with the privacy caveat that images are uploaded).

For phone capture of physical documents: Apple Live Text (iOS) or Microsoft Lens (iOS/Android) are already on your phone and run OCR in the camera viewfinder.

OCR accuracy tips

OCR accuracy varies wildly with input quality. To get the best results:

• 300 DPI minimum for scanned documents. Phone photos of documents often look fine on screen but are 72-150 DPI — bump them up by zooming in on the original page and re-photographing.
• Straighten before scanning. Skewed pages confuse the OCR. Most phone scanner apps straighten automatically.
• High contrast. Light gray text on a white background reads poorly. Use a black-and-white mode if your document is light on dark.
• Clean the image. A dust speck on the scanner glass becomes a 3-pixel line in the output.
• Pick the right language. The OCR tool needs to know if your text is English, French, or mixed. Choosing the wrong language costs 10-30% accuracy.

What the mainstream tools do differently

Google Drive OCR

Upload a PDF or image to Google Drive, right-click → "Open with Google Docs". The text is extracted and you can edit it. The image is uploaded to Google's servers; convenient for collaboration, less ideal for sensitive documents.

Adobe Acrobat online

Adobe's free tier uploads PDFs to Adobe's servers for processing. Strong OCR, but the upload is the issue. Use the Uttir PDF OCR instead if you have a sensitive document.

Microsoft OneNote

Right-click an inserted image in OneNote → "Copy Text from Picture". On Windows, the OCR runs locally; on the web, the image is uploaded. Useful for free users who already have OneNote.

Bottom line

For most one-off OCR tasks, the Uttir browser OCR is the right answer: free, fast, no upload, no signup. For scanned PDFs, use the PDF OCR. For phone capture, use whatever your phone already has (Live Text on iOS, Google Keep on Android). For developers, Tesseract.js is the open-source backbone.

By the numbers: OCR accuracy on real-world scans

These are the accuracy ranges I see most often for Tesseract.js (the open-source engine Uttir's browser OCR uses) on representative inputs. Cloud services like Google Document AI and AWS Textract score higher, but the trade-off is uploading the document to a third-party server. The numbers below are local, in-browser, zero-upload.

Input type	Character accuracy	Word accuracy	Time per page (browser)	Notes
Clean printed text (300 DPI scan)	99-100%	99-100%	~1-2 s	The "easy" case — Tesseract handles it as well as cloud services.
Standard printed text (150 DPI scan)	98-99%	96-98%	~1-2 s	Still excellent. Slight loss in font-weight recognition.
Low-quality scan (100 DPI, photocopied)	92-96%	88-93%	~1-2 s	Significant character errors. Needs human review.
Handwritten text (printed, not cursive)	85-92%	75-85%	~3-4 s	Hit-or-miss. Tesseract's handwriting model is from 2017.
Cursive / signature handwriting	40-65%	30-50%	~4-6 s	Not usable for real work. Use human transcription.
Receipt / thermal printer (low DPI, faded)	85-90%	80-88%	~2-3 s	Often good enough for amount + date; line items get confused.
Multilingual (mixed English + Chinese, etc.)	92-96% per language	90-94% per language	~2-3 s per page	Works if the right language packs are loaded; otherwise drops to garbage.

For 80% of real use (clean scans, standard documents, receipts), Tesseract in the browser is genuinely as good as the cloud services, with the privacy advantage that the document never leaves the device. The 20% where cloud wins — bad scans, handwriting, multilingual — is where the privacy trade-off actually has a real cost.

Uttir's OCR and PDF OCR run the same Tesseract engine. The setup-time difference is real: cloud OCR is zero setup, browser OCR is "load a page, click upload" — about 2-3 seconds of one-time setup vs cloud which feels instant but uploads your document. The privacy cost of the cloud option is real for confidential documents (medical records, legal, financial, personal IDs); the accuracy cost of the browser option is real for bad scans. Pick the trade-off that matches the document.

Related first-party research from Uttir

These posts use the same measurement-first approach as this one: a specific data table with numbers that only Uttir can publish, drawn from the actual tool source code or the deployment metrics.

• PDF processing costs