AWS Textract vs Google Vision OCR Compared

Last updated August 2026.

AWS Textract and Google Cloud Vision charge exactly the same headline rate for plain OCR, $1.50 per 1,000 pages, and return very different things for the money. Vision gives you text and where it sits on the page. Textract gives you text plus document structure: tables, form key-value pairs, and answers to questions you ask about the page. If all you need is the words, Vision is the simpler and cheaper choice at low volume because its 1,000 free units per month never expire. If you need the layout, Vision cannot do it at any price and you are choosing Textract or Google Document AI instead.

AWS Textract vs Google Vision OCR at a glance

Every figure below was read from the vendor pricing and documentation pages in August 2026. Textract prices are for US West (Oregon); AWS rates vary slightly by region.

Which is cheaper, Textract or Google Vision?

For raw text extraction they cost the same until you get large. Both charge $1.50 per 1,000 pages and both drop to $0.60 per 1,000 at their top tier. The difference is where that tier starts: Textract reaches the discount after 1 million pages a month, Google after 5 million. Process 3 million pages a month and Textract bills roughly $2,700 while Vision bills $4,500.

At the other end, Vision is meaningfully cheaper for anything small. Its 1,000 free units per month are permanent, so a low-volume job can run at zero cost forever. The Textract free tier is 1,000 DetectDocumentText pages per month for your first three months, after which every page is billed. A side project that scans 400 documents a month is free on Vision and about $0.60 a month on Textract, which is not a lot of money but is a real difference in setup friction.

One billing detail catches people out on Vision: a unit is one image with one feature applied. Ask for TEXT_DETECTION and LABEL_DETECTION on the same image and you are billed two units. Each page of a multi-page PDF also counts as its own image. Textract bills straightforwardly per page, and its final 1,000-unit block is not prorated the way Google prorates its last block.

What does Google Vision OCR actually return?

Vision returns the full text of the image plus a nested hierarchy of pages, blocks, paragraphs, words and individual symbols, each with a bounding box and a confidence score. DOCUMENT_TEXT_DETECTION is the variant tuned for dense documents and it auto-detects the full set of supported languages, where TEXT_DETECTION auto-detects only a subset and is aimed at sparse text in photographs.

What it does not return is meaning. There is no table object, no key-value pair, no notion that the string next to Total is the total. You get accurate words in accurate positions and the job of reconstructing structure from coordinates is yours. Teams underestimate that job constantly. Rebuilding a table from bounding boxes works on clean, well-ruled layouts and falls apart on the merged cells, wrapped text and skewed scans that real documents are full of.

Does Google Vision extract tables from documents?

No. Cloud Vision OCR has no table extraction feature. It returns text with coordinates, and any table structure has to be inferred from those coordinates by your own code. Google puts table and form extraction in Document AI, a separate product with separate pricing, which is the direct comparison to Textract AnalyzeDocument rather than Vision.

This is the single most common reason a Vision project stalls. The API is easy to call, the text comes back looking great, and then someone asks for the line items and the engineering estimate triples. If tables are in scope, compare Vision against Document AI before writing any geometry code.

Is AWS Textract better than Google Vision?

For structured documents, yes, because it does things Vision cannot. Textract returns tables as row and column objects, form fields as key-value pairs, and with Queries you can ask "what is the invoice number" and get an answer rather than coordinates. For plain multilingual text extraction, no. Textract officially supports six languages and English-only handwriting; Vision covers well over 200 languages and handwriting in six scripts.

Put plainly: pick by what the document is, not by which cloud you like. A Spanish invoice with a line-item table goes to Textract. A Japanese menu photo, a Cyrillic form, or a Thai receipt goes to Vision, because Textract will not read it at all.

Can AWS Textract read handwriting?

Yes, Textract recognizes both printed and handwritten characters, but handwriting recognition is supported in English only. Text has to be at least 15 pixels tall, roughly 8 point at 150 DPI, and vertical text is not supported. Vision supports handwriting across six scripts, with Latin, Japanese and Korean fully supported and Bengali, Cyrillic, Devanagari, Greek, Chinese and Vietnamese marked experimental.

The file handling differences that decide real projects

These limits matter more than the price for most teams, and they are the part nobody reads until something breaks in production.

The Cloud Storage requirement is the one that reshapes an architecture. If a user uploads a PDF to your app and you want text back, Vision means writing the file to a bucket, calling the async endpoint, polling for completion, and reading the JSON output back out of another bucket. Textract will take the same PDF as bytes in a single synchronous call if it is one page. That difference is worth more than a few cents per thousand pages when you are estimating build time.

What about receipts and invoices specifically?

Neither raw OCR product is the right tool. Vision has no receipt model at all. Textract has AnalyzeExpense at $0.01 per page, which returns vendor, date, totals and line items as labelled fields, and that is the correct comparison point. On the Google side the equivalent is the Document AI Expense parser, which bills $0.10 per document where one count covers up to 10 pages. A one-page receipt therefore costs ten times more on Google than on Textract, while a ten-page invoice costs the same on both. A lot of published comparisons quote Google at $10 per 1,000 pages and get this backwards.

We keep the current per-page rates for all the major providers on our OCR API pricing page, and the head-to-head write-ups sit at Textract vs Document AI and AWS Textract alternatives.

How to choose in five minutes

• You need words only, in any language, at low volume. Google Cloud Vision. The permanent free tier and the 200-plus language coverage decide it.
• You need tables or form fields. AWS Textract, or Google Document AI. Vision is out.
• You are extracting receipts or invoices. Textract AnalyzeExpense at $0.01 per page, or a finished extraction tool if you do not want to build a pipeline.
• You process more than a million pages a month. Textract, because its volume discount starts five times earlier.
• Your documents are not in English, French, German, Italian, Portuguese or Spanish. Vision, because Textract does not support them.
• You want a spreadsheet rather than a JSON pipeline. Neither. Both are developer APIs that assume you are writing code around them.

The part that comes after the API call

Both services stop at JSON, and the JSON still has to land somewhere useful. That is the work teams forget to budget: mapping fields, handling the documents that come back wrong, storing images alongside the parsed values, and pushing the result into a ledger, a warehouse or an accounting system. Unless you already run a data integration layer that can absorb a new source without a bespoke job, that plumbing usually costs more engineering time than the extraction itself.

Which is the honest case for skipping the API entirely when your documents are receipts and invoices. If the goal is a clean spreadsheet rather than a service, our receipt OCR API returns parsed fields directly, and the receipt to Excel converter hands back a finished file with no code at all. Choose Textract or Vision when you are building a product around document data. Choose a finished tool when you just need the numbers out of the paper.