# Azure Document Intelligence vs Google Cloud Document AI

> Google Cloud Document AI scores 73.9 (BB) to Azure Document Intelligence's 66 (B) for document parsing. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai
- Markdown: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.md (~3,100 tokens)
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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

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.

- Azure Document Intelligence: grade B, 66/100, rank #305 of 950. Markdown https://www.anchorterminal.com/tools/azure-document-intelligence.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json
- Google Cloud Document AI: grade BB, 73.9/100, rank #82 of 950. Markdown https://www.anchorterminal.com/tools/google-cloud-document-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/google-cloud-document-ai.json
- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md
- All 109 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md

## 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

| Category | Weight | Azure Document Intelligence | Google Cloud Document AI | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 82 | 90 | Google Cloud Document AI +8 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 86 | 81 | Azure Document Intelligence +5 |
| Agent ergonomics | 13% (16.2 this run) | 64 | 70 | Google Cloud Document AI +6 |
| Security & auth | 14% (17.5 this run) | 71 | 80 | Google Cloud Document AI +9 |
| Payments & pricing | 10% (12.5 this run) | 20 | 20 | even |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 40 | 80 | Google Cloud Document AI +40 |
| Transparency & trust | 7% (8.8 this run) | 78 | 90 | Google Cloud Document AI +12 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **66 · B** | **73.9 · BB** | |

## Facts side by side

| Fact | Azure Document Intelligence | Google Cloud Document AI |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Microsoft Azure | Google Cloud |
| Hosted endpoint | no (local only) | no (local only) |
| Transports | HTTP | HTTP |
| Auth | OAuth or key | OAuth |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | Proprietary service under Microsoft's Product Terms. The client libraries are MIT | Proprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-10-06 | 2026-10-08 |
| Terms last updated | no date given | 2026-09-02 |
| Privacy policy last updated | 2026-09-01 | 2026-09-28 |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | not found in the text |
| Popularity | 386k npm/wk, 2.1M PyPI/wk | 499k 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.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "azure-document-intelligence", "b": "google-cloud-document-ai"}`. From a terminal: `anchor compare azure-document-intelligence google-cloud-document-ai`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json and https://www.anchorterminal.com/api/v1/tools/google-cloud-document-ai.json

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