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OpenParser

One OCR API over nine hosted models — typed blocks, markdown, and schema extraction with citations

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paidPrepaid credits with per-page rates published per model and $10 of free credits at signup, no subscription tier. The cheapest engine, PaddleOCR-VL 1.6, is $1 per 1,000 pages; Azure DI Read is $1.73; Mistral OCR 3 is $2.30; Mistral OCR 4 is $4.60; Azure DI Layout is $11.50. Parse meters pages at the retail rate of whichever ocr_model the request names, and option surcharges are published live on GET /models/ocr. The /extract endpoint adds LLM token costs billed at the rate of the llm_model selected, on top of the page rate. Prices are in US dollars.View full pricing →

Visit OpenParser

https://www.openparser.dev

About OpenParser

OpenParser is a document-parsing API whose selling point is model choice rather than a single house OCR engine. Nine hosted OCR models sit behind one request shape: PaddleOCR-VL, two generations of Mistral OCR, Azure Document Intelligence Layout and Read, Google enterprise document engines and AWS Textract among them. You change the `ocr_model` field and nothing else about your integration, which is a direct answer to the usual failure mode of document pipelines — the engine you standardised on turns out to be wrong for one document class and switching means rewriting the integration. Two endpoints carry the product. POST /parse returns a typed `openparser@1` block structure plus markdown, where blocks carry a kind (text, table, field, checkbox, signature), page number, bounding box and confidence. POST /extract fills a schema you supply and cites the block ids each value came from, so a downstream reviewer can trace any extracted field back to its position on the page. Sync, async and batch requests share the same request shape, with GET /jobs/{id} for async status and GET /files/{id}/content for reusable file bytes. Idempotency keys are supported on parse. Pricing is per page and published per model, which makes cost routing an explicit design decision: send bulk general documents to the cheapest open-weight engine and reserve the expensive enterprise engines for the layout-heavy exceptions.

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Key Features

Nine hosted OCR engines swappable via one request field
Typed openparser@1 blocks with bounding boxes and confidence scores
Schema extraction that cites the source block id for every value
Sync, async and batch share one request shape
Idempotency keys on parse requests
Per-model page rates published live via the API

OpenParser Pros & Cons

Pros

  • +Cost routing per document class is a first-class feature, not a workaround
  • +Citations back to block ids make extracted fields auditable
  • +No subscription — credits and per-page rates only

⚠️ Cons

  • You are responsible for choosing the right engine per document type
  • Extraction costs stack page rates and LLM token rates together
  • Thin abstraction means provider-specific output quirks still surface

Tags

ocrdocument-parsingpdfapistructured-extractiondeveloper-tools
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