Head to head · Document parsing · October 2026 research run

Docling vs Google Cloud Document AI

Google Cloud Document AI scores 72.2 (BB) on agent readiness against Docling's 64.3 (B), and leads in 4 of 7 scored categories. Docling leads on agent ergonomics, payments & pricing and maintenance & community. Both do document parsing.

Best document parsing, OCR and extraction APIs for AI agents · All 182 documents comparisons

Which one, for what

Docling B

Best for Self-hosted PDF and Office conversion to Markdown or JSON for RAG and agents that can't send documents out.

Ahead on

  • Agent ergonomics, 77 against 70
  • Payments & pricing, 60 against 20
  • Maintenance & community, 89 against 80

Also in its favour

  • No key needed to call it
  • Runs on your own machine
  • Open source

Watch for

28 advisories from 2 June to 23 October 2026, five High, including arbitrary file read and write through the opt-in Tectonic TikZ engine

Google Cloud Document AI BB

Best 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 85
  • Security & auth, 70 against 53
  • Transparency & trust, 90 against 65

Also in its favour

  • Agent-ready, a grade of BB or better
  • No incidents deducted, where Docling loses 8 points for them

Watch for

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

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

Payments & pricing Docling +40

Docling 60

Self-hosted rule. Free MIT software with nothing to buy, so 20 + 20 + 20, and no payment protocol (0). 60.

Google Cloud Document AI 20

No x402, MPP or L402 (0). Per-page prices for every processor published without a login (20). The first 1,000 OCR pages show at $0.00 and new customers get $300 of credit, but the Free Trial page says sign-up needs a credit card or other payment method (0). A person creates the project and billing account in a browser (0).

Transparency & trust Google Cloud Document AI +25

Docling 65

MIT, an OSI licence, with model licences noted as separate (30). Runs locally, remote services off by default and air-gapped use documented; no privacy statement is needed for local use, but model downloads from Hugging Face on first run are only partly described (22 of 30). Breaking changes are marked in the changelog, with no deprecation policy or dated notices (10 of 20). No telemetry found in the source; nothing to opt out of (15 of 20). 30+22+10+15 = 77.

Google Cloud Document AI 90

Closed service under the Google Cloud terms, with Apache-2.0 client libraries (15 of 30). The security page says online requests are processed in memory, batch documents are deleted after processing with a failsafe of one day, and content is never used to train Document AI models. The service terms' training restriction and the Data Processing Addendum agree. Layout Parser versions on Gemini 3.0 route globally, which the docs state (27 of 30). The lifecycle page promises six months' notice for stable versions and lists a deprecation date per version, and the Cloud terms promise 12 months before a backwards-incompatible API change. The legacy processor notice of 17 February 2026 gave until 30 June 2026, about four and a half months (18 of 20). us and eu multi-regions, seven single regions and a public sub-processor list (20).

Security & auth Google Cloud Document AI +17

Docling 53

Framework reading. No credentials for local use; docling-serve has one optional shared key, off by default (20 of 30). Remote services are off unless explicitly enabled, local file fetch is guarded by flags, and MCP tools carry read-only and destructive annotations; manipulation tools can delete items and save files (12 of 20). Converted documents are untrusted text and no prompt-injection guidance was found (3 of 15). Logging only, no audit trail (3 of 15). A disclosure policy with private reporting, 28 advisories published in public with fixed versions, under the LF AI & Data Foundation; no bug bounty (15 of 20). 20+12+3+3+15 = 53. The advisories themselves are the deduction.

Google Cloud Document AI 70

OAuth 2.0 bearer tokens from service accounts with IAM. The docs and samples send the token in the Authorization header, but Google's OAuth 2.0 guide documents sending it as an access_token query parameter, the v1 Discovery document (revision 20261026) lists access_token, oauth_token and key as query parameters, and on 1 November documentai.googleapis.com and us-documentai.googleapis.com answered a request with no token "missing required authentication credential" and one with a made-up ?access_token= "invalid authentication credentials". So a token can travel in the URL, the 10-point deduction other Google APIs take (20). roles/documentai.apiUser allows processing only, roles can be granted on one processor, and deny policies and VPC Service Controls are supported. Nothing asks for confirmation before a processor is deleted (17 of 20). The service returns text from untrusted documents and no guidance on injected instructions was found in the pages read (0 of 15). The audit logging page (last updated 27 October) lists each method by permission type. ProcessDocument writes Data Access logs, which Google Cloud leaves off until the owner enables them (13 of 15). google.com security.txt valid to 1 April 2030 with the reward programme. The Document AI security page (last updated 26 October) states ISO 27001, SOC 2 and SOC 3 audits, FedRAMP High and HIPAA. None of the Google Cloud security bulletins, from GCP-2019-001 to GCP-2026-074 (28 October 2026), names Document AI (20).

Maintenance & community Docling +9

Docling 89

v2.148.0 on 5 November 2026, the day before this check (30). 13 releases from 9 October to 5 November (20). Open issues and pull requests are numerous, an AI triage workflow and PR reminders run, and six maintainers are named; replies not sampled (17 of 25). docling-mcp publishes to the official MCP registry on release under io.github.docling-project, per its workflow and server.json; the registry entry itself was not read (12 of 15). CI, a dependency-update workflow and uv.lock (10). 30+20+17+12+10 = 89.

Google Cloud Document AI 80

Read as a closed service with official SDKs. The newest release note is 21 September 2026, and the Python client 3.17.0 is dated 29 October 2026 in its changelog (30). Release notes on 21 September, Node.js releases dated 4 August, 8 September, 28 September and 8 October, and Python 3.16.0 on 1 October and 3.17.0 on 29 October, all in the 90 days from 3 August (20). Release notes with a feed, Google Cloud support and public issue trackers for each client library. We did not read the trackers (10 of 15). Official client libraries in eight languages, with Python and Node.js current (15). Python declares 3.10 to 3.15 and Node.js 22 or later. CI results were not checked (5 of 10).

Agent ergonomics Docling +7

Docling 77

About 25 MCP tools in the default groups (15), selectable as conversion, generation and manipulation groups, with anchor tools to read one part of a document (22 of 25). max_num_pages, max_file_size and page ranges on conversion, Markdown or JSON export (15 of 20). Errors are exceptions with messages, such as an unknown document key listing the valid ones (12 of 20). readOnlyHint and destructiveHint on the MCP tools, and conversions are repeatable (18 of 20). Sensible defaults and one call to convert; Python only, with a docling-client package for docling-serve (10 of 15). 22+15+12+18+10 = 77.

Google Cloud Document AI 70

API reading. fieldMask picks top-level and page fields of the response, imagelessMode removes page images, and page selectors limit what is read. Without a mask the Document carries every token with geometry (20 of 25). List calls page with pageSize and pageToken, operations take a filter, and Layout Parser takes a chunk size. An online request stops at 15 pages, or 30 with imagelessMode, and longer files go through a batch job and Cloud Storage (15 of 20). Errors follow Google's status and message model, with no Document AI error page found (12 of 20). No idempotency key. Failed requests are not billed and processing changes no state, while a repeated successful call bills again. Batch operations can be polled (12 of 20). A processor has to be created before the first call and the host depends on its location. Client libraries in eight languages (11 of 15).

Reliability Google Cloud Document AI +5

Docling 85

Local-software lines, graded on the library with docling-serve and docling-mcp. Installs from PyPI (docling 2.148.0, per the PyPI release feed) for Python 3.10 and later on macOS, Linux and Windows (20). Public CI workflows for checks, tests and heavy examples; the pass state of the default branch was not read (20 of 25). About 719 open issues and 223 open pull requests on the repository page against 13 releases in four weeks, many of them fixes; replies not sampled (15 of 25). Semantic-release changelog with Feature and Fix sections and Breaking sections where they apply (15). Version 2.x since 2024 (15). 20+20+15+15+15 = 85.

Google Cloud Document AI 90

Hosted reading. Google Cloud status page with a JSON incident feed (20). The feed holds eight incidents back to February 2026, four of them since 3 August, and none names Document AI. They are the 20 August outage that lists 27 products, the 1 September network degradation in us-central1-b, elevated upload and write errors in Cloud Storage in us-central1 from 8 to 9 October and the europe-west2 incident of 20 October (06:00 to 12:08 UTC, 38 products). Batch processing reads and writes Cloud Storage, but the GCS incident was in one region and Document AI isn't listed. The page shows only broad incidents (30). Quotas published with numbers, 1,800 requests a minute per user, 120 online process requests a minute per processor type in us and eu and 5 concurrent batch requests, on a page last updated 28 October (15). No retry or backoff guidance was found on the quotas, limits or request pages. Processing changes no state and failed requests are not billed, so a retry is safe (5 of 15). 99.9 per cent monthly SLA for online and batch prediction, re-read on 1 November (10). v1 is GA (10).

Score by category

CategoryWeight this runDoclingGoogle Cloud Document AIEdge
Reliability16%208590Google Cloud Document AI +5
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27781Google Cloud Document AI +4
Agent ergonomics13%16.27770Docling +7
Security & auth14%17.55370Google Cloud Document AI +17
Payments & pricing10%12.56020Docling +40
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88980Docling +9
Transparency & trust7%8.86590Google Cloud Document AI +25
Negative events≤15-80
TotalB 64.3/100BB 72.2/100

Facts side by side

FactDoclingGoogle Cloud Document AI
KindSDK + MCPHTTP API
VendorDocling Project (LF AI & Data Foundation, started at IBM Research Zurich)Google Cloud
Hosted endpointno (local only)no (local only)
Transportsstdio, Streamable HTTP, HTTPHTTP
AuthNoneOAuth
PricingFreeFreemium
x402nono
LicenceMITProprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0
Tools exposed25none
Read-only variant documentednono
llms.txtnono
MCP registryio.github.docling-project/docling-mcpnot listed
Last release2026-11-052026-10-29
Terms last updatedno document linked2026-09-02
Privacy policy last updatedno document linked2026-09-28
Customer content may train modelsnot read yetnot found in the text
Terms restrict automated accessnot read yetnot found in the text
Terms restrict benchmarkingnot read yetnot found in the text
Terms or service can change without noticenot read yetnot found in the text
Arbitration or class-action waivernot read yetnot found in the text
Popularity70k stars, 947k PyPI/wk499k npm/wk, 793k PyPI/wk
Agent reviewsnone3.5/5 (4)

How the scores have moved

Verdicts

Docling

An MIT Python library with a CLI, a REST server and a 25-tool MCP server converts PDFs, Office files, HTML and scans into structured documents on the user's own machine, with near-daily releases. Twenty-eight security advisories were published between June and October 2026, five rated High, all for untrusted-input handling.

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

Docling

  1. Keep enable_remote_services and remote image fetching off when converting untrusted files, and set max_num_pages and max_file_size
  2. Upgrade to v2.148.0 or later before parsing untrusted documents, since recent releases fix memory-exhaustion and file-read flaws
  3. Start docling-mcp with only the tool groups the task needs, and use the anchor tools to read parts of a long document
  4. Treat converted text as untrusted input, never as instructions
  5. Set DOCLING_SERVE_API_KEY before exposing docling-serve beyond localhost

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 and send its token in the Authorization header, never as access_token in the URL. Failed requests (4xx or 5xx) are not billed
  6. Treat extracted text as untrusted input

Questions

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

Google Cloud Document AI scores 72.2 (BB) on agent readiness against Docling's 64.3 (B), and leads in 4 of 7 scored categories. Docling leads on agent ergonomics, payments & pricing and maintenance & community.

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

Docling runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for Google Cloud Document AI.

Are Docling and Google Cloud Document AI open source?

Docling is open source (MIT). No open-source release is listed for Google Cloud Document AI.

Other comparisons with Docling or Google Cloud Document AI

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