Why is AWS Textract expensive at high volume?

Its AnalyzeDocument features are priced per page per feature and add up: Tables $15, Queries $15 and Forms $50 per 1,000 pages for the first million pages a month, falling to $10, $10 and $40 above one million. Extracting forms, tables and queries from two million pages costs $125,000 a month by AWS's own example. Plain text detection is cheap at $1.50 per 1,000 pages ($0.60 above one million), so the cost lands on structured extraction.

Is it hard to migrate off Textract?

The API swap is the easy part; the output model is not. Textract returns Block objects (WORD, LINE, KEY_VALUE_SET, TABLE, CELL) with relationships, while Mistral OCR, Reducto and Docling return markdown or JSON and Azure and Google return their own document schemas. Budget for rewriting the parsing layer, re-running a labelled sample of your documents through both systems and comparing field accuracy before switching traffic. Reducto offers up to $5,000 in migration credits for teams moving from another document processor.

Can I keep data inside AWS without Textract?

Yes. Docling and PaddleOCR run on your own EC2 or EKS GPUs at zero per-page cost, and Mistral OCR is available as a self-hosted container under an enterprise agreement. Reducto offers VPC and on-prem deployments on its Enterprise plan. These keep documents inside your account while avoiding Textract's per-feature pricing.

Quick Answer

Best AWS Textract Alternatives for High-Volume Documents

Q: What are the best AWS Textract alternatives for high-volume document processing?

As of October 2026: Mistral OCR 4.1 is the cheapest structured alternative at $4 per 1,000 pages ($2 with batch), returning markdown, tables, bounding boxes and confidence scores. Azure Document Intelligence ($10 per 1,000 pages for layout or prebuilt models) and Google Document AI ($10 for Layout Parser, $1.50 for Enterprise OCR) are the like-for-like cloud swaps. Reducto ($10 parse, $20 extract per 1,000 pages, 20% off batch) is the accuracy pick for messy documents. Docling is the free open-source option for air-gapped or very high volumes. Textract itself costs $15 per 1,000 pages for tables and $50 for forms on the first million pages.

Published: October 8, 2026

The short answer

For high-volume pipelines, Mistral OCR 4.1 is the default Textract replacement: $4 per 1,000 pages ($2 batch) against $15–$70 for Textract’s structured features. Pick Azure Document Intelligence or Google Document AI for a like-for-like managed cloud swap with prebuilt invoice and ID models, Reducto when accuracy on messy documents matters more than price, LlamaParse for RAG ingestion, and Docling when the per-page cost has to be zero. Prices are list USD per 1,000 pages, read October 8, 2026.

What Textract costs you today

Textract feature	First 1M pages/month	Above 1M
Detect Document Text	$1.50	$0.60
AnalyzeDocument — Tables	$15	$10
AnalyzeDocument — Queries	$15	$10
AnalyzeDocument — Forms	$50	$40
Forms + Tables + Queries	$70	$55

AWS’s own pricing example: forms, tables and queries on two million pay stubs a month costs $125,000. That bill is what an alternative has to beat.

The alternatives

Alternative	Price per 1,000 pages (list)	Output	Deployment	Best for
Mistral OCR 4.1	$4 · batch $2 · Document AI annotations $5	Markdown, tables, paragraph boxes, block labels, confidence	API; self-hosted container (enterprise)	Lowest cost with structure
Azure Document Intelligence	Read $1.50 · layout/prebuilt $10 · custom $30	JSON fields with confidence	Azure; disconnected containers	Microsoft shops, prebuilt forms
Google Document AI	Enterprise OCR $1.50 ($0.60 >5M) · Layout Parser $10 · Custom Extractor $30 ($20 >1M)	Document JSON, entities with confidence	Google Cloud	Custom schemas, few training docs
Reducto	Parse $10 · Extract $20 · Deep Extract $40 · 20% off batch	Blocks, markdown, schema JSON with citations	API; VPC/on-prem (Enterprise)	Hardest documents, audit trails
LlamaParse	Credits: 1,000 credits = $1.25; tiered by parse mode	Markdown, JSON, XLSX	SaaS or hybrid (Enterprise)	RAG ingestion, 130+ file types
Docling (open source)	$0 + your compute	Markdown, JSON, DocTags	Anywhere	Air-gapped, unlimited volume

What each costs at 1 million pages a month

For a forms-and-tables workload of 1,000,000 pages a month at list price:

Textract Forms + Tables: $65,000
Reducto Extract: $20,000 ($16,000 batch)
Azure prebuilt or layout: $10,000
Google Layout Parser: $10,000; Custom Extractor $30,000
Mistral OCR 4.1: $4,000 ($2,000 batch)
Docling on your own GPUs: compute only

These are not equal outputs — Mistral and Docling return parsed documents, so field extraction becomes your code or a cheap LLM pass, while Textract Forms, Azure prebuilt and Reducto Extract return fields. Even adding an LLM extraction pass, the parse-then-extract pattern usually lands well under Textract’s Forms price.

Provider notes

Mistral OCR 4.1. Paragraph-level bounding boxes, structural block labels and block-level confidence scores at $4 per 1,000 pages, half that through the Batch API. The best price-to-structure ratio on this list; an enterprise self-hosted container keeps data in your VPC.

Azure Document Intelligence and Google Document AI. The closest functional matches to Textract: prebuilt processors for invoices, receipts and IDs, custom extractors trained on your documents, and per-field confidence. Choose the one where your data and cloud commitment already live.

Reducto. Prices took effect September 1, 2026. Extract returns every field with page, bounding box, source text and confidence; batch jobs get 20% off with a 12-hour completion guarantee. Up to $5,000 in migration credits for teams leaving another processor.

LlamaParse. Credit-based (1,000 credits = $1.25) with Free (10K credits), Starter (40K) and Pro (400K) plans and an Auto Mode that routes each page to the cheapest adequate tier. Strongest when the destination is a RAG index.

Docling. IBM-originated, actively released open-source parser. Zero licence cost, runs on CPU or GPU, and is the usual base layer for teams processing tens of millions of pages.

How to choose

Cost is the reason you’re leaving: Mistral OCR 4.1 batch, plus field validation in code.
You use Textract Forms/AnalyzeExpense/AnalyzeID: Azure or Google prebuilt models.
Accuracy complaints on messy scans: Reducto Extract or Deep Extract.
Data cannot leave your network: Docling, or Mistral’s self-hosted container.

Run 500–1,000 of your own pages through two candidates and Textract, and compare field-level accuracy before moving traffic. The full ranking is in best OCR and document extraction APIs; architecture for millions of pages is in best OCR pipeline for large-scale extraction.

Last verified: October 8, 2026. Prices are list USD; volume and committed-use discounts differ.