What is the best OCR API in 2026?

For most developers, Mistral OCR 4 (released June 23, 2026) is the best default: it topped the OlmOCRBench leaderboard at launch, reads 170 languages, returns markdown with tables, formulas, bounding boxes and confidence scores, and costs $4 per 1,000 pages ($2 via the Batch API). For invoices, receipts, IDs and forms with prebuilt schemas, Google Document AI and Azure Document Intelligence remain the safest enterprise picks at $10 per 1,000 pages for prebuilt models. For hard, messy PDFs where extraction accuracy matters more than price, Reducto's r-1 Parse at $10 per 1,000 pages leads.

What is the cheapest OCR API per page in 2026?

Google Document AI's Enterprise Document OCR at $1.50 per 1,000 pages (falling to $0.60 above 5 million pages a month), and Azure Document Intelligence's Read API and AWS Textract's Detect Document Text, both $1.50 per 1,000 pages, are the cheapest managed text-only OCR. LlamaParse's Fast tier works out to about $1.25 per 1,000 pages (1 credit per page at $1.25 per 1,000 credits) with 10,000 free credits a month. Open-source Docling, Marker or PaddleOCR are free apart from compute.

OCR vs document extraction API — what is the difference?

OCR turns pixels into text and layout (markdown, reading order, tables). Document extraction goes a step further and returns structured fields — invoice number, line items, dates — as JSON against a schema. Mistral's Document AI ($5 per 1,000 pages), Google and Azure prebuilt/custom extractors ($10–$30 per 1,000 pages), Reducto Extract ($20 per 1,000 pages all-in from September 1, 2026) and LlamaParse's Agentic tiers are extraction products; the Read/Detect endpoints and Mistral OCR 4 alone are OCR.

Should I use a frontier LLM instead of an OCR API?

For low volumes and one-off documents a vision-capable frontier model (GPT-6 Astra, Claude Fable 5.1, Gemini 3.8 Flash) can read pages directly, but per page it is usually more expensive than a dedicated OCR API, slower, and gives no bounding boxes or confidence scores. The common 2026 pattern is OCR API first for layout-faithful markdown, then an LLM over the text for reasoning and extraction — which is exactly what Mistral Document AI, Reducto Extract and LlamaParse Agentic do under the hood.

Quick Answer

Best OCR & Document Extraction APIs 2026: 7 Ranked

Published: September 14, 2026

The short answer

Ranked for developers who need reliable text and structure out of PDFs, scans and photos in 2026, weighing accuracy, price, features and operational fit:

Rank	API	Best for	Price per 1,000 pages (Sep 2026)	Free tier
1	Mistral OCR 4	Best default: accuracy, languages, markdown + bboxes at a low price	$4 standard · $2 batch · $5 Document AI (schema JSON)	Trial credits
2	Google Document AI	Cheapest scalable text OCR; prebuilt invoice/receipt/W-2 parsers	$1.50 Enterprise OCR ($0.60 >5M/mo) · $10 layout/prebuilt · $30 custom ($20 at volume)	$300 GCP credit
3	Azure Document Intelligence	Microsoft shops; prebuilt + custom models; add-ons (formulas, barcodes, query fields)	$1.50 Read · $10 layout/prebuilt · $30 custom extraction · $50 custom classification	500 pages/mo (first 2 pages per doc)
4	Reducto	Hardest documents; agentic extraction with the best accuracy on messy PDFs	$10 r-1 Parse · $20 Extract · $40 Deep Extract · $7.50 Classify · 20% off batch	$150 credit
5	LlamaParse (LlamaIndex)	RAG pipelines; generous free tier; tiered speed/accuracy	~$1.25 Fast · ~$3.75 Cost-effective · ~$12.50 Agentic · ~$56 Agentic Plus	10,000 credits/mo
6	AWS Textract	AWS-native pipelines; forms, tables, queries, IDs, expenses	$1.50 Detect Text · $15 Tables · $15 Queries · $50 Forms (first 1M pages)	1,000 pages/mo for 3 months
7	Open source: Docling, Marker, PaddleOCR	Air-gapped, high-volume, zero per-page cost	$0 + GPU/CPU compute	Unlimited

Rule of thumb: text-only at scale → Google or Azure Read at $1.50; general-purpose markdown with layout → Mistral OCR 4 at $4 ($2 batch); structured fields from ugly documents → Reducto; RAG ingestion on a budget → LlamaParse; nothing may leave the building → Docling.

1. Mistral OCR 4 — the best default

Released June 23, 2026, OCR 4 topped the OlmOCRBench leaderboard at launch (85.20), reads 170 languages, and returns markdown that preserves reading order, tables, images and math, plus bounding boxes and confidence scores — the two features developers most missed in OCR 3. Throughput is up to ~2,000 pages per minute per GPU. Pricing is $4 per 1,000 pages, $2 with the Batch API, and $5 per 1,000 pages for Document AI, which wraps OCR 4 with a schema-driven pass that returns custom JSON. OCR 4.1 entered public preview on July 16, 2026 with region-specific pricing around €3.50–€4.38 per 1,000 pages.

Why it ranks first: it is the only API that combines frontier accuracy, markdown-native output, bounding boxes and a sub-$5 price. Why not for everyone: no prebuilt invoice/receipt/ID processors, and EU-hosted by default — check data-residency needs.

2. Google Document AI — cheapest at scale, strongest prebuilt library

Google’s Enterprise Document OCR at $1.50 per 1,000 pages (dropping to $0.60 above 5 million pages a month) is the cheapest way to turn scans into text at volume, and the basic Read API is $0.65. Layout Parser and prebuilt processors (invoice, receipt, expense, W-2, bank statement, ID) cost $10 per 1,000 pages; Custom Extractor is $30 ($20 at volume) with neural training at $3/hour after 10 free hours a month. It is the pick when you process millions of pages or need a prebuilt processor for a US tax or finance form.

3. Azure Document Intelligence — the Microsoft-native choice

Same shape as Google with Azure economics: Read (OCR only) $1.50 per 1,000 pages, Layout and prebuilt models (invoice, receipt, ID, contract, health insurance card) $10, custom extraction $30, custom classification $50, plus add-ons for high-resolution, formulas, barcodes and query fields at $6–$10 per 1,000 pages or 20–30% surcharges. Free tier: 500 pages a month, limited to the first two pages of any file and 4 MB. Choose it for Microsoft 365 / Fabric / Copilot Studio integration and Azure compliance boundaries.

4. Reducto — accuracy on the documents that break everyone else

Reducto is what teams switch to after Azure or Google mangles a 300-page scanned contract with rotated tables. Its r-1 Parse returns text, layout, tables and OCR for $10 per 1,000 pages; from September 1, 2026 pricing is per endpoint with one credit = $0.01: Extract $20 per 1,000 pages all-in (down from $45 under the old parse-plus-extract structure, with a more accurate model), Deep Extract $40, Split $20, Deep Split $40, Classify $7.50, Edit $60 ($15 for fully prefilled pages). Batch jobs get 20% off; new accounts get $150 free. It is the most expensive managed option per page and, on hard documents, usually the cheapest per correct field.

5. LlamaParse — built for RAG, generous free tier

LlamaIndex’s parser is priced in credits: $1.25 per 1,000 credits, with Fast at 1 credit/page (spatial text only), Cost-effective at 3, Agentic at 10 and Agentic Plus at 45 — roughly $1.25, $3.75, $12.50 and $56 per 1,000 pages. The free tier is 10,000 credits a month; Starter is $50/month for 40,000 credits, Pro $500/month for 400,000. Layout extraction and enriched forms output add per-page credits. It is the natural pick if you already build on LlamaIndex or want to prototype ingestion at zero cost.

6. AWS Textract — for AWS-native pipelines

Textract remains the default inside AWS: Detect Document Text $1.50 per 1,000 pages (first million), Tables $15, Queries $15, Forms $50, plus AnalyzeID and AnalyzeExpense for IDs and receipts. It has not matched Mistral or Reducto on accuracy for complex layouts, but S3 triggers, IAM and Step Functions integration keep it in a lot of production stacks. Free tier: 1,000 pages a month for three months.

7. Open source — Docling, Marker, PaddleOCR

When data cannot leave your network or volume makes any per-page fee painful: Docling (IBM; PDF/DOCX/PPTX → markdown/JSON with table structure and a vision-language option), Marker (fast PDF → markdown with optional LLM cleanup), and PaddleOCR (multilingual detection and recognition, strong on CJK). Cost is compute only; you own accuracy tuning, scaling and upgrades. Many teams run Docling for bulk ingestion and route the 5% of hard pages to Reducto or Mistral.

How to choose in 60 seconds

What do you need back? Plain text → Google/Azure Read ($1.50). Markdown with tables and boxes → Mistral OCR 4 ($4/$2). Structured JSON → Mistral Document AI ($5), prebuilt parsers ($10), Reducto Extract ($20).
How ugly are the documents? Clean digital PDFs → anything. Scans, handwriting, rotated tables, 100+ pages → Reducto or Mistral.
Volume? Under 10,000 pages a month → LlamaParse free tier or Mistral trial. Millions → Google’s $0.60 tier or open source.
Where must data live? Azure/AWS/GCP compliance boundary → the matching cloud API. On-prem only → Docling.

Last verified: September 14, 2026. Prices are list USD per 1,000 pages from vendor pricing pages; volume discounts apply.