Browser OCR vs Cloud OCR

What you're actually choosing

"OCR" lumps together a dozen different problems: typed text, handwriting, tables, columns, multi-language, low-resolution scans, photos taken on a phone. The right answer depends on which of these you're hitting most often. Our Screenshot to Text and PDF to Clean Text tools both run Tesseract in your browser — fast for the common cases, free, private.

Side-by-side

When browser OCR is right

• You're handling sensitive documents — contracts, medical, financial — and can't ship them to a third party.
• You only OCR a few documents a week. Cloud signup overhead isn't worth it.
• The text is clearly printed at decent resolution.
• You're building a tool that should "just work" with no API key.

When cloud OCR is right

• You need handwriting recognition (forms, signatures, notes).
• The documents are tables that must keep their structure (invoices, statements).
• Volume is high enough that 2s/page browser-side becomes a UX problem.
• You're already inside the AWS/GCP/Azure ecosystem and want IAM-managed access.

The hybrid play

Run browser OCR first as the default. If confidence is low (Tesseract reports it per word), fall back to cloud OCR. You get free + private for the easy 80% and accurate cloud results only when you need them. Batch Document Extractor is where this pattern usually lands first — bulk PDFs and images through a single pipeline.

And the third option: vision LLMs

GPT-4 Vision, Claude 3.5 Sonnet, and Gemini 1.5 Pro all do OCR as a side effect. They're slower and pricier per page than dedicated OCR APIs, but they understand context — so a chart, diagram, or weird layout often comes out as usable structured data instead of raw text. See our deep-dive on OCR vs vision models for the trade-offs.