Google Document AI reads 15 pages online (30 with imageless mode) and up to 1,000 pages per file in batch, with a 40 MB online and 1 GB batch file size. The 15-page online cap is what triggers the page-limit error.
The online endpoint stops at 15 pages, which is the surprise on the first long document. Here is every Document AI limit, read from Google's docs. Last updated July 2026.
Upload a document to extract
Drop files here or click to upload
Up to 50 files
Uploading...
Read a document past 15 pages without an online-versus-batch decision.
Google Document AI has two processing modes and the split defines its limits. Online processing, the synchronous ProcessDocument call, accepts a file up to 40 MB and 15 pages, or 30 pages if you enable imageless mode. That 15-page cap is the lowest single-request page ceiling in the cloud OCR group, and it is exactly what raises the PAGE_LIMIT_EXCEEDED error the first time you send a long document. Batch processing, the asynchronous BatchProcessDocuments call, reads a file up to 1 GB and up to 1,000 pages depending on the processor, with as many as 5,000 files in a single request pulled from a Cloud Storage bucket. Quotas such as 5 concurrent batch requests per project and roughly 120 pages per minute of provisioned throughput are adjustable in the Cloud console, while the content limits above are system limits that cannot be changed. Everything here is read from the Google documentation in July 2026, so confirm each figure on the current limits and quotas pages before you design around it.
The first long document is where teams meet the limit. You send a 20-page contract to the online ProcessDocument endpoint and get back PAGE_LIMIT_EXCEEDED. That is expected. Online processing is built for an immediate, synchronous response, so it caps at 15 pages, or 30 if you enable imageless mode, which skips returning rendered page images and processes pages contiguously from page 1.
For anything longer you move to batch processing. You put the file in a Cloud Storage bucket, call BatchProcessDocuments, and Google reads up to 1,000 pages per file, writing the results back to Storage. A single batch request handles up to 5,000 files, and you can run 5 concurrent batch requests per project. Batch is where Document AI actually scales; the online endpoint is for short, interactive requests.
The 15-page cap itself is not the cost. The cost is the plumbing it forces once your documents cross it: a Cloud Storage bucket, an async batch call, polling the long-running operation, and reading results back out of Storage. For a team already on Google Cloud that is routine. For everyone else it is real integration work to read a document that a product would take as one upload.
Page and file-size caps are system limits and cannot be raised. Throughput and concurrency quotas are adjustable in the Cloud console. Verified from Google docs, July 2026.
The same limits split by mode, because which one you use decides your page ceiling and your architecture.
| Limit | Online (sync) | Batch (async) |
|---|---|---|
| Max file size | 40 MB | 1 GB per file (from Cloud Storage) |
| Max pages | 15 (30 with imageless mode) | 100 to 1,000, varies by processor |
| Max files per request | 1 | 5,000 |
| Result | Returned in the response | Written to Cloud Storage, poll the job |
| Input source | Bytes or Cloud Storage | Cloud Storage only |
| Best for | Short docs, immediate response | Long docs, high volume |
See how these ceilings compare with Azure and AWS on the OCR API limits comparison, and what Document AI costs per 1,000 pages on the Google Document AI pricing breakdown.
Concurrency and throughput are adjustable quotas. The page and file-size caps above are fixed system limits.
| Quota | Value |
|---|---|
| Concurrent batch requests | 5 per project (US, EU, regional). |
| Provisioned throughput (base) | About 120 pages per minute. |
| Provisioned throughput (Pro base) | About 30 pages per minute. |
| Image resolution | 40 megapixels per page. |
| Imageless mode | Raises online cap to 30 pages, contiguous from page 1. |
| System vs quota limits | File size and page caps are fixed; throughput quotas adjustable. |
If your documents routinely run past 15 pages and you would rather not build the batch job, a Google Document AI alternative that reads a long PDF in one upload skips the online-versus-batch decision entirely.
Fix the 15-page online error, step by step.
Google next to Azure, Textract, Mistral and Gemini.
The 1-page sync vs 3,000-page async split.
500 MB, 2,000 pages, and the free F0 two-page cap.
Per-processor rates and the 10-page block trap.
Skip the online-versus-batch decision on long PDFs.
How the two clouds compare on limits and output.
Per-1,000-page rates across the market.
An honest roundup for US teams.
Google's online cap means a Cloud Storage bucket, a batch call and polling the moment a document runs long. DocuOCR takes the whole PDF in one upload, reads every page, and returns clean fields. Drop in your longest document and compare.