OCR API Limits: Max File Size and Page Limits Compared

Textract splits sync and async, so it appears twice: one page synchronously, 3,000 pages asynchronously. Azure lists free and paid tiers separately because the free F0 tier returns only the first 2 pages. Google lists online and batch because the online 15-page cap is the limit most teams hit. For the AWS numbers in depth, see the AWS Textract limits page, and for what each of these costs, the OCR API pricing comparison.

What is the maximum file size for an OCR API?

It ranges from 20 MB to 1 GB depending on the vendor. AWS Textract accepts 10 MB synchronously and 500 MB asynchronously. Azure AI Document Intelligence takes 500 MB per request on the paid tier. Google Document AI allows 40 MB online and 1 GB in batch. Mistral Document AI and the Gemini API cap PDFs at 50 MB, and Google Cloud Vision limits an image to 20 MB. Always confirm the current figure on the vendor doc, since these change.

How many pages can an OCR API process in one request?

The single-request ceiling runs from 15 pages to 3,000. AWS Textract reads up to 3,000 pages in an asynchronous PDF job but only 1 page synchronously. Azure AI Document Intelligence takes 2,000 pages in one analyze call. Google Document AI allows 15 pages online, or up to 1,000 pages per file in batch. Mistral Document AI and Gemini both cap at 1,000 pages. So the answer depends heavily on whether you call the synchronous or the asynchronous endpoint.

Why does AWS Textract only read one page?

Because the synchronous Textract operations, DetectDocumentText and AnalyzeDocument, accept a single-page PDF or TIFF, or one image, up to 10 MB. To read a multi-page PDF you call the asynchronous operations, StartDocumentTextDetection or StartDocumentAnalysis, which accept up to 3,000 pages and 500 MB from Amazon S3, then you poll the JobId for the result. Sending a multi-page PDF to the synchronous call is the most common Textract error, and the fix is to switch to the async job.

What is the Google Document AI page limit?

Google Document AI processes up to 15 pages per document with online (synchronous) processing, or 30 pages if you enable imageless mode. The maximum online file size is 40 MB. For anything larger you use batch (asynchronous) processing, which handles up to 1,000 pages per file depending on the processor, files up to 1 GB, and up to 5,000 files per batch request. The 15-page online cap is what triggers the "page limit exceeded" error most teams hit first.

Which OCR API handles the largest documents?

For raw page count, AWS Textract wins with a 3,000-page asynchronous limit, ahead of Azure AI Document Intelligence at 2,000 pages in a single call. For file size, Google Document AI batch accepts the largest single file at 1 GB, ahead of Azure and Textract at 500 MB. The LLM based readers, Mistral Document AI and Gemini, are the most constrained at 50 MB and 1,000 pages, which matters when your scanned PDFs are large.

Do OCR APIs have rate limits?

Yes. Azure AI Document Intelligence defaults to 15 analyze transactions per second on the paid S0 tier and 1 on the free F0 tier, both raised by support request for S0. Google Document AI meters pages per minute and allows 5 concurrent batch requests per project. AWS Textract publishes per-second transaction quotas in the Service Quotas console that vary by operation and Region. Build retry logic with exponential backoff, because a 429 response means you crossed a per-second limit, not that your document was rejected.

What file formats do OCR APIs accept?

The common set is PDF, JPEG, PNG and TIFF. Azure AI Document Intelligence adds BMP and HEIF, and reads DOCX, PPTX and XLSX with its Read and Layout models but not with prebuilt or custom models. AWS Textract accepts JPEG, PNG, PDF and TIFF but rejects XFA-based and password-protected PDFs. Mistral Document AI also reads PPTX, DOCX and AVIF. Confirm format support per model, because a prebuilt or custom model often accepts fewer types than plain OCR.

What is the free tier page limit?

Free tiers are built for testing, not volume. Azure AI Document Intelligence free F0 returns only the first 2 pages of any request and caps files at 4 MB. Google and AWS give a monthly free allowance or a new-customer credit on their OCR engines rather than a page-per-request cap. Because the free tiers truncate or meter so tightly, run your real multi-page documents on a paid key before you judge accuracy at length.

Does the page limit change accuracy or just capacity?

It changes capacity, not accuracy. The page and file-size limits govern how much you can send in one request, not how well the model reads a page. That said, hitting a limit forces an architecture choice, synchronous versus asynchronous, that affects latency and complexity. A 12-page PDF is fine for Azure in one call, needs batch on Google, and needs an async job on Textract, so the limit shapes your integration even though the per-page result is the same.

How do I process a PDF larger than the API limit?

Split it or go asynchronous. If your PDF exceeds the online page cap, most commonly Google Document AI at 15 pages, switch to the batch or async endpoint, which raises the ceiling to 1,000 to 3,000 pages. If it exceeds the file-size cap, split the PDF into chunks under the limit, process each, and stitch the results by page number. A product with built-in batching and a review queue does this splitting and reassembly for you.

Which OCR API should I choose based on limits?

Match the limit to your documents. For long PDFs of hundreds of pages, Azure in one call or Textract async are the least fiddly. For very large files near a gigabyte, Google Document AI batch has the most headroom. For short documents where you want a synchronous answer, any of them works, but remember Textract sync is one page. If you would rather not manage sync-versus-async, page splitting and polling yourself, a ready-to-use product handles the limits and hands you clean fields.