Summarize this article with:
- Choose Mistral OCR 4 for multilingual OCR, complex layouts, self-hosting, and one of the strongest price-to-feature ratios.
- Choose Google Document AI when you need specialized processors for invoices, IDs, forms, or complex tables.
- Choose Azure AI Document Intelligence for Microsoft environments, private deployments, and container-based processing.
- Choose Veryfi or Affinda for specialized use cases: financial documents for Veryfi, resumes and CVs for Affinda.
- Choose Eden AI to compare multiple providers, add automatic fallback, standardize responses, and route eligible workloads through EU infrastructure.
Mistral released OCR 4 on June 23, 2026. It hit HackerNews hard (436 points, 113 comments) and landed as one of the biggest AI releases of the week. The claim: document intelligence that matches or beats the legacy OCR providers at a fraction of the price.
But how does it actually compare to Google Document AI, AWS Textract, Azure AI Document Intelligence, and specialist players like Mindee, Veryfi, and Affinda? We dug into features, benchmarks, pricing, and integration options for each. Here's what we found.
What's New in Mistral OCR 4
Mistral OCR 4 is the fourth generation of Mistral's OCR line. OCR 3 came out in December 2025. The model ID is mistral-ocr-4-0, and the mistral-ocr-latest alias now points to this version.
Six things changed from OCR 3:
- Bounding boxes. Paragraph-level coordinates for every extracted text block. This was their most-requested feature. You can now highlight exactly where on the page each piece of text came from. Useful for data pipelines and audit trails.
- Block classification. Each extracted block gets a type label: title, table, equation, signature, image. You get semantically labeled structure, not just raw text.
- Inline confidence scores. Per-page and per-word confidence levels. You can set quality gates: reject anything below 95% confidence, flag the 80-95% range for human review. That's how production OCR pipelines actually work.
- 170 languages. The widest multilingual coverage in the category. Mistral pulls ahead most clearly in low-resource languages where competitors tend to fall apart.
- Single-container self-hosting. Deploy OCR 4 in one Docker container on your own infrastructure. For organizations that can't send documents to a third-party API, that's a big deal.
- Structured document output. Beyond markdown, the API returns bounding boxes plus classification plus confidence per block. Suitable for RAG ingestion, agentic pipelines, or enterprise search indexing.
Mistral OCR 4 Benchmarks
Mistral published official scores:
- OlmOCRBench: 85.20 (top overall)
- OmniDocBench: 93.07 (strong on complex documents)
- Crawl Multilingual (internal): 0.98 across all 8 language groups
- Human blind evaluation: 72% average win rate across 600+ real-world documents, 12+ languages, against all leading OCR and document AI systems
Rogo, a financial services company, reported that OCR 4 matched leading agentic document parsers on accuracy while running at roughly 8x lower cost and 17x lower latency on chart-heavy financial documents.
Mistral OCR 4 Pricing
- Standard API: $4 per 1,000 pages
- Batch API: $2 per 1,000 pages (50% discount for async)
- Throughput: Up to 2,000 pages per minute
Page-based pricing, not token-based. You know the cost before you start processing.
Supported Formats
PDF (primary), DOC/DOCX, PPT/PPTX, OpenDocument formats, and images (scanned documents, photos of text).
What It Doesn't Do
Mistral says OCR 4 isn't meant for medical diagnosis, legal judgment, high-stakes financial decisions, safety-critical systems, or latency-sensitive real-time processing. It's a document understanding model, not a decision engine.
Mistral OCR 4 Main Competitors in 2026
The main competitors of Mistral OCR 4 are Google Document AI, Amazon Textract, Azure AI Document Intelligence, Mindee, Veryfi and Affinda. Here's how the six main competitors break down on pricing, features, and best-use scenarios.
Google Document AI
Google Document AI offers 100+ pre-trained processors covering invoices, mortgages, health insurance cards, and more. In December 2025 they released the Gemini-powered Layout Parser v1.6, which significantly improved complex table extraction.
Pricing per 1,000 pages:
- Enterprise Document OCR: $1.50 (drops to $0.60 at 5M+ pages/month)
- Layout Parser (Gemini-powered): $10.00
- Form Parser: $30.00
- Free tier: 1,000 pages/month plus $300 GCP credits
Accuracy: Around 92% field-level extraction. The Gemini Layout Parser handles complex tables and multi-column layouts well.
Best for: Teams already in the Google Cloud ecosystem. The Gemini integration is the most significant technical advancement in document parsing in the last year.
Data residency: US and EU multi-region available. GDPR-compliant via DPA. Subject to the US CLOUD Act.
AWS Amazon Textract
Amazon Textract five distinct APIs: basic text detection, table analysis, form analysis, queries, and signatures. Tight integration with S3, Lambda, and Step Functions.
Pricing per 1,000 pages:
- Basic text detection: $1.50
- Table analysis: $15.00
- Form analysis: $50.00
- Queries: $10.00 | Signatures: $5.00
- Tables + Forms combined: $65.00
- Free tier: 1,000 pages/month for 3 months
Best for: AWS-native stacks. If your data lives in S3 and your compute runs on Lambda, Textract plugs in with minimal friction.
Data residency: 15+ AWS regions including EU (Frankfurt, Ireland). GDPR via DPA. Subject to the US CLOUD Act.
Azure AI Document Intelligence
Microsoft rebranded this into Azure AI Foundry Tools in 2025 and added new document field extraction in early 2026.
Pricing per 1,000 pages:
- Prebuilt models (invoice, receipt, ID, layout): $10.00
- Custom neural models: $20-$40
- Basic OCR (Read): $1.00
- Free tier: 500 pages/month plus 10 free custom training hours/month
Accuracy: Around 95%+ on prebuilt models. Competitive with Google on standard documents.
Best for: Organizations that need on-prem or edge deployment. Azure offers container deployment for fully on-prem processing where no data leaves your network. Among the big three cloud providers, that's the strongest GDPR play.
Data residency: 25+ Azure regions including multiple EU regions. Container option for on-prem. GDPR via Microsoft DPA.
Mindee
Mindee is a French company with a developer-first approach. Featured in multiple Best OCR API roundups in 2026 for balancing ease, pricing, and documentation quality.
Pricing:
- Free: 250 pages/month (no credit card)
- Starter: EUR 44/month for 500 pages
- Pay-as-you-go: $0.10/page
- Pro/Business/Enterprise: custom
Best for: EU-sensitive workloads. Mindee is a French company, which means no US CLOUD Act exposure. Data stays in the EU by default. SOC 2 compliant.
Data residency: EU or US hosting selectable. GDPR-native by design.
Veryfi
Verify is the accuracy leader for financial documents. In their 2025 benchmark of 500 invoices, they hit 98.7% field-level accuracy with 2.8-second average latency.
Pricing:
- Expense Management App: $19.99/month (300 receipts)
- Starter API: $500/month
- Per-document: roughly $0.05-$0.50 depending on type
Accuracy: 98.7% field-level on invoices. 99.56% line-item accuracy on receipts. Sub-3-second latency.
Best for: Financial document processing where accuracy is non-negotiable. The Veryfi Lens mobile SDK is also the strongest option for real-time mobile receipt capture.
Data residency: US-based (Sunnyvale, CA). SOC 2 Type II. GDPR via DPA but subject to CLOUD Act. No EU-native hosting.
Affinda
Affinda is Australian company that launched an Agentic AI Platform in September 2025 with persistent model memory and RAG-based instant correction (no retraining needed). In December 2025, they released a no-code Integration Agent connecting to 2,800+ systems.
Pricing:
- Starter: approximately $99/month (~1,000 pages)
- Pay-per-parse: approximately $0.10-$0.13
Accuracy: Claims above 95%. The agentic AI enables continuous improvement via RAG.
Best for: Resume and CV parsing (their flagship product, 56 languages, 80+ countries). First IDP vendor to combine RAG with agentic AI.
Data residency: HQ Melbourne, Australia. Multi-region available. GDPR via DPA. Not subject to US CLOUD Act.
Mistral OCR 4 Pricing Comparison
Mistral OCR 4 at $4/1,000 pages is roughly 16x cheaper than AWS Textract for forms+tables processing. It costs more than Google's basic OCR ($1.50), but adds layout understanding, bounding boxes, and block classification that basic OCR doesn't include.
The sweet spot: you get layout-aware extraction comparable to Google's $10 Layout Parser at less than half the price.
Use Case Matching
Not every document parsing task is the same. Here's which provider leads in each category.
- Invoices and receipts: Veryfi (98.7% accuracy) or Google Document AI (specialized processors). Mistral OCR 4 handles general invoices but lacks the specialized field extraction Veryfi trained on 100M+ documents.
- Financial documents (bank statements, W-2, 1099): Google Document AI has the most pre-trained financial processors. AWS Textract's Analyze Lending handles mortgage and lending documents specifically.
- IDs and passports: Google Document AI and Azure Doc Intelligence both have strong pre-built ID parsers. Mindee's passport and ID APIs are clean and well-documented.
- Resumes and CVs: Affinda leads here. Resume parsing is their flagship product with 56 languages and 80+ countries.
- Complex layouts and tables: Google's Gemini Layout Parser is strongest. Mistral OCR 4's block classification competes but is newer and less tested in production.
- Multi-language documents: Mistral OCR 4 at 170 languages has the widest coverage. Most competitors top out around 50-100 languages.
- High-volume batch processing: Mistral OCR 4 (2,000 pages/minute) and Azure Doc Intelligence both handle volume. Mistral's batch API at $2/1,000 pages is the cheapest async option.
- On-prem deployment: Azure Doc Intelligence (containers) and Mistral OCR 4 (single Docker container). No other provider offers self-hosting.
Calling These APIs Through a Unified Endpoint
Managing separate API keys, response formats, and billing accounts for six different document parsing providers gets messy fast. API gateways solve this.
Eden AI is a French AI API gateway that unifies 10+ document parsing providers behind a single API:
import requests
from concurrent.futures import ThreadPoolExecutor
url = "https://api.edenai.run/v3/universal-ai"
headers = {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
}
# Compare multiple OCR providers in parallel
providers = ["google", "microsoft", "amazon", "mindee"]
def call_ocr(provider):
payload = {
"model": f"ocr/ocr/{provider}",
"input": {
"file_url": "https://example.com/invoice.pdf"
}
}
resp = requests.post(url, json=payload, headers=headers)
return provider, resp.json()
with ThreadPoolExecutor() as pool:
results = dict(pool.map(call_ocr, providers))
for provider, result in results.items():
print(f"{provider}: {result.get('text', '')[:100]}")
- One API key and one billing account instead of managing six vendor relationships.
- Standardized response format from every provider. Switching providers means changing a string in your payload, not rewriting your parsing logic.
- Multi-provider comparison: send the same document to five providers at once and compare accuracy, latency, and cost.
- Automatic fallback: if one provider fails or times out, the request routes to a backup.
- EU data residency: Eden AI is a French company with a dedicated EU endpoint. Data stays in Europe. GDPR-compliant by design.
For teams evaluating Mistral OCR 4 against alternatives, the multi-provider call is the fastest way to benchmark. Send your test documents through the gateway, compare results, and pick based on data instead of marketing claims.
Data Residency and GDPR
This matters more in 2026 than it did in 2024. The EU AI Act enforcement timeline is active, and the CLOUD Act continues to create friction for non-US companies using US-based AI providers.
EU-native (no CLOUD Act exposure):
- Mistral AI (French company, EU-hosted)
- Mindee (French company, EU or US selectable)
- EdenAI gateway (French company, dedicated EU endpoint)
EU regions available (but subject to CLOUD Act):
- Google Document AI (EU multi-region)
- AWS Textract (Frankfurt, Ireland)
- Azure AI Document Intelligence (multiple EU regions)
On-prem capable (data never leaves your network):
- Azure AI Document Intelligence (container deployment)
- Mistral OCR 4 (single Docker container, self-hosted)
US-only:
- Veryfi (no EU hosting option)
For organizations processing sensitive documents under GDPR, the options narrow quickly. If you need EU data residency with no CLOUD Act exposure, you're looking at Mistral, Mindee, or routing through EdenAI. If you need on-prem, it's Azure containers or self-hosting Mistral.
Which Should You Choose?
There's no single best document parsing API. The right pick depends on your use case, volume, budget, and compliance requirements.
- Mistral OCR 4 if you want the best price-to-features ratio, need multilingual support (170 languages), want bounding boxes and block classification, or need self-hosting. At $4/1,000 pages for layout-aware extraction, it's hard to beat.
- Google Document AI if you're already in the Google Cloud ecosystem, need specialized processors for specific document types (100+ available), or want the Gemini Layout Parser for complex tables.
- AWS Textract if your stack is AWS-native and you need tight S3/Lambda/Step Functions integration. Just know it's the most expensive option at $65/1,000 pages for forms+tables.
- Azure AI Document Intelligence if you need on-prem deployment via containers, want the best value among the big three ($10/1,000 pages), or need Microsoft ecosystem integration.
- Mindee if you're EU-based and want GDPR-native processing with no CLOUD Act exposure.
- Veryfi if you're processing financial documents and accuracy can't slip. 98.7% field-level accuracy is the highest in the category.
- Affinda if you're parsing resumes/CVs at scale, or you want the agentic AI approach with continuous improvement via RAG.
- EdenAI if you want to evaluate multiple providers without building six separate integrations, need automatic fallback for production reliability, or want EU data residency with access to both EU and US providers through one API.
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