LandingAI Agentic Document Extraction vs Mistral OCR: which is better?

As of October 2026, Mistral OCR 4.1 is the better default for high-volume parsing into markdown: $4 per 1,000 pages ($2 with the Batch API), bounding boxes, block labels and confidence scores, 170 languages and a self-hostable container for enterprise customers. LandingAI Agentic Document Extraction (ADE Gen2, DPT-3 models) is the better pick when every extracted value must be traceable: it returns line-level (DPT-3 Pro) or word-level (DPT-3 Verity) grounding with word confidence, and its Extract API returns citations back to the word on the page.

How much does LandingAI Agentic Document Extraction cost per page?

ADE uses credits at $0.01 each on the Explore and Team plans. DPT-3 Pro parsing costs 1 credit per page plus 0.5 credits per 1,000 output characters on the Priority tier, and half that (0.5 + 0.25) on the asynchronous Standard tier. DPT-3 Verity costs 0.3 + 0.2 (Priority) or 0.15 + 0.1 (Standard). A dense page of about 3,000 characters therefore costs about $12.50 per 1,000 pages with Pro on Standard and about $4.50 with Verity on Standard. Extract is billed separately by input and output characters.

How much does Mistral OCR cost?

Mistral OCR 4.1 (model ID mistral-ocr-4-1, generally available since July 2026) costs $4 per 1,000 pages through the API and $2 per 1,000 with the Batch API. Document AI with schema-based annotations is $5 per 1,000 pages. Self-managed deployment is available to enterprise customers on request.

Which is more enterprise-ready, LandingAI or Mistral OCR?

Both are. LandingAI's Team plan (credit packs from $250 a month) includes zero data retention and a HIPAA BAA, and Enterprise adds SSO, SLAs and deployment in your VPC on AWS, Azure or Google Cloud, in Snowflake, or on-premises including air-gapped. Mistral OCR runs in a single container for fully self-hosted deployments, which is the simplest path for data-sovereignty requirements, but self-hosting is an enterprise agreement, not a self-serve option.

Quick Answer

LandingAI Agentic Document Extraction vs Mistral OCR (2026)

Published: October 7, 2026

The short answer

Pick Mistral OCR 4.1 if you need cheap, fast, multilingual parsing of many documents into markdown. Pick LandingAI Agentic Document Extraction (ADE) if you need structured fields where every value can be traced to a word or line on the page. As of October 7, 2026, Mistral is the lower-cost default; LandingAI costs more on dense pages and is built for audit trails, review screens and regulated workflows.

Side-by-side (October 2026)

	LandingAI ADE Gen2	Mistral OCR 4.1
Current models	DPT-3 Pro (default) · DPT-3 Verity (public preview)	`mistral-ocr-4-1` (GA, released July 2026; `mistral-ocr-latest` points to it)
Main output	Markdown with hierarchical blocks, tables as HTML, stable block IDs	Markdown/text with typed blocks (titles, tables, equations, signatures)
Grounding	Table-cell boxes; line-level (Pro) or word-level with word confidence (Verity)	Paragraph-level bounding boxes, block labels, block-level confidence
Field extraction	Extract API with any JSON schema; atomic citations back to the word	Document AI annotations against your schema
Pricing	$0.01/credit · Pro: 1 credit/page + 0.5/1K output chars (Priority), half on Standard	$4 per 1,000 pages · $2 Batch · $5 Document AI annotations
Typical cost, dense page (~3,000 chars)	≈ $25/1K pages (Pro, Priority) · ≈ $12.50 (Pro, Standard) · ≈ $4.50 (Verity, Standard)	$4/1K pages · $2 batch
Large jobs	Async Parse Jobs up to 6,000 pages or 1 GB per PDF	Batch API
Languages	Multilingual; Pro handles non-Latin scripts, handwriting, formulas	170 languages across 10 language groups
Deployment	US + EU cloud; Enterprise: your VPC (AWS, Azure, GCP), Snowflake, on-prem, air-gapped	API; single-container self-hosting for enterprise customers
Compliance on self-serve	Team plan: zero data retention, HIPAA BAA	Enterprise agreement for self-hosting

The cost rows are our arithmetic from LandingAI’s published credit rates; LandingAI says a typical business document parsed with DPT-3 Pro uses a median of 1.5 credits on the Standard tier. Run your own documents — the bill depends on how many characters each page returns.

Features: where each one wins

LandingAI’s advantage is traceability. Gen2 replaced the old chunk output with pages → blocks → lines → words, each with a stable ID, a markdown span pointer and a bounding box. DPT-3 Verity adds a confidence score for every word. The Extract API then returns citations drawn from that grounding, so a value such as “invoice total” points to the exact word on the exact page. That is what you need to build a human-review UI, redact PII at the word level, or prove to an auditor where a number came from.

Mistral’s advantage is throughput per dollar. OCR 4 (June 2026) added bounding boxes, block classification and inline confidence; 4.1 (July 2026) moved to paragraph-level boxes and block-level confidence scores. Mistral reports the top OlmOCRBench score of 85.20 for OCR 4 and a 72% average human-preference win rate against competing systems — vendor numbers, but consistent with independent leaderboards that place it near the top.

Accuracy

Neither vendor publishes a score on a shared benchmark with the other. For digitally created PDFs both are close to exact. The difference shows up on scans, handwriting, checkboxes and dense tables: LandingAI’s DPT-3 Pro reads layout first and handles handwritten pages and formulas; Mistral 4.1 improved checkbox styles, right-to-left tables and missed blocks on complex pages. Test 50–100 of your own worst documents and score the fields you actually use.

Use cases: the pick

Your job	Pick
RAG ingestion of millions of pages	Mistral OCR 4.1 (Batch, $2/1K)
Invoices, claims, KYC with field-level audit trail	LandingAI ADE (Extract + atomic citations)
Human review UI with low-confidence highlighting	LandingAI ADE (DPT-3 Verity word confidence)
Multilingual archives, low-resource languages	Mistral OCR 4.1
Data must stay in your own cluster	Either: Mistral container or LandingAI on-prem — both via enterprise contract
Documents already in Snowflake	LandingAI ADE (Snowflake deployment option)

Migration warning

LandingAI says code written for ADE Gen1 will not work with Gen2: the response structure changed (chunks became blocks) and Parse pricing moved from a flat 3 credits per page to complexity-based credits. Budget a migration if you are on DPT-2.

The full field of document APIs is ranked in best OCR and document extraction APIs; for citation-grade JSON specifically, see best PDF OCR API for structured JSON with page citations, and for vendor selection at company scale, best enterprise AI OCR and document processing.

Last verified: October 7, 2026. Prices are list USD from the vendors’ pricing pages and documentation.