Head to head · Document parsing · October 2026 research run

Azure Document Intelligence vs Google Cloud Document AI

Google Cloud Document AI scores 73.9 (BB) on agent readiness against Azure Document Intelligence's 66 (B), and leads in 5 of 7 scored categories. Azure Document Intelligence leads on schema & documentation. Both do document parsing.

Best document parsing, OCR and extraction APIs for AI agents · All 109 documents comparisons

Which one, for what

Azure Document Intelligence B

Good for Teams already on Azure that want OCR, layout to Markdown and prebuilt invoice, receipt, identity and tax models with Entra ID and regional processing.

Ahead on

  • Schema & documentation, 86 against 81

Watch for

Every analysis is asynchronous. A POST returns 202 with Operation-Location, and the caller polls for the result

Google Cloud Document AI BB

Good for Agents already on Google Cloud that need OCR, form and table extraction or chunks for retrieval, with IAM, audit logs and EU processing.

Ahead on

  • Reliability, 90 against 82
  • Agent ergonomics, 70 against 64
  • Security & auth, 80 against 71
  • Maintenance & community, 80 against 40
  • Transparency & trust, 90 against 78

Also in its favour

  • Agent-ready, a grade of BB or better

Watch for

An online request reads at most 15 pages (30 with imagelessMode). Longer files need a batch job through Cloud Storage

Score by category

CategoryWeight this runAzure Document IntelligenceGoogle Cloud Document AIEdge
Reliability16%208290Google Cloud Document AI +8
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28681Azure Document Intelligence +5
Agent ergonomics13%16.26470Google Cloud Document AI +6
Security & auth14%17.57180Google Cloud Document AI +9
Payments & pricing10%12.52020even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84080Google Cloud Document AI +40
Transparency & trust7%8.87890Google Cloud Document AI +12
Negative events≤1500
Total66 · B73.9 · BB

Facts side by side

FactAzure Document IntelligenceGoogle Cloud Document AI
KindHTTP APIHTTP API
VendorMicrosoft AzureGoogle Cloud
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP
AuthOAuth or keyOAuth
PricingFreemiumFreemium
x402nono
LicenceProprietary service under Microsoft's Product Terms. The client libraries are MITProprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0
Read-only variant documentednono
llms.txtnono
Last release2026-10-062026-10-08
Terms last updatedno date given2026-09-02
Privacy policy last updated2026-09-012026-09-28
Customer content may train modelsyesnot found in the text
Terms restrict automated accessyesnot found in the text
Terms restrict benchmarkingyesnot found in the text
Terms or service can change without noticenot found in the textnot found in the text
Arbitration or class-action waivernot found in the textnot found in the text
Popularity386k npm/wk, 2.1M PyPI/wk499k npm/wk, 793k PyPI/wk

Verdicts

Azure Document Intelligence

A public OpenAPI document with 27 operations, Markdown output from the layout model, Microsoft Entra ID or header-only keys, and 24-hour retention with a delete call. Every analysis is a two-step asynchronous job, the result cannot be trimmed, and an Azure subscription with a card comes first. Three of the four SDKs last shipped in 2025 or earlier.

Google Cloud Document AI

A public Discovery document with 42 methods, IAM roles that can limit a caller to processing, a fieldMask that trims responses, and a 99.9 per cent SLA on the US and EU endpoints. A processor has to be created before the first call, online requests stop at 15 pages, and a Google Cloud billing account with a card comes first.

Before you call either

Azure Document Intelligence

  1. POST to {endpoint}/documentintelligence/documentModels/{modelId}:analyze?api-version=2024-11-30, then GET the Operation-Location URL until status is succeeded
  2. Wait at least 2 seconds between polls and follow the Retry-After header. Default limits are 15 analyse calls and 50 result reads a second on S0
  3. Use prebuilt-read for plain text at $1.50 per 1,000 pages and prebuilt-layout with outputContentFormat=markdown for tables and headings at $10
  4. Set pages (for example 1-3,5) to limit both the bill and the response size. F0 stops at two pages per request
  5. Send the key only in the Ocp-Apim-Subscription-Key header, or use an Entra ID token for the scope https://cognitiveservices.azure.com/.default
  6. Treat extracted text as untrusted input. Results expire 24 hours after the job completes

Google Cloud Document AI

  1. Create a processor first (processors.create or the console), then POST to https://LOCATION-documentai.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/processors/PROCESSOR_ID:process
  2. Use the host that matches the processor's location, us-documentai.googleapis.com or eu-documentai.googleapis.com
  3. Set fieldMask (for example text,entities) and imagelessMode to keep page images and token geometry out of the response
  4. Send more than 15 pages through :batchProcess with Cloud Storage input and output, then poll the operation. Jobs unfinished after 24 hours are cancelled
  5. Grant the service account roles/documentai.apiUser only. Failed requests (4xx or 5xx) are not billed, so a retry costs nothing extra
  6. Treat extracted text as untrusted input

Questions

Which is better for AI agents, Azure Document Intelligence or Google Cloud Document AI?

Google Cloud Document AI scores 73.9 (BB) on agent readiness against Azure Document Intelligence's 66 (B), and leads in 5 of 7 scored categories. Azure Document Intelligence leads on schema & documentation.

Do Azure Document Intelligence and Google Cloud Document AI need an API key?

Azure Document Intelligence takes an API key or an OAuth sign-in. Google Cloud Document AI uses an OAuth sign-in.

Can an agent call Azure Document Intelligence and Google Cloud Document AI without installing anything?

No hosted endpoint is listed for Azure Document Intelligence. No hosted endpoint is listed for Google Cloud Document AI.

Other comparisons with Azure Document Intelligence or Google Cloud Document AI

Machine-readable

For companies

Do agents find, use and choose your tools?

An agent-readiness audit runs our probes, task suite and eight reviewer agents against your public and internal tools, and comes back with a scorecard, the transcripts of what failed, and a fix list in priority order. From $2,500, re-run included. We never take payment to move a rank. We do help companies earn one.