Mistral OCR alternative for teams that need fields and CSV, not only Markdown
PdfParse is a Mistral OCR alternative for US developers who need named fields, CSV tables and JSON from a PDF, not only page Markdown. Mistral OCR turns pages into Markdown with tables and images at a low per page rate, so it stays the better pick for raw text at volume. PdfParse fits when your code still has to find the invoice total, split a table into rows and decide which values to trust.
Parse your own PDF before you switch
Start with an invoice or scan from your actual workflow. Inspect fields, text and tables against the source before changing your integration.
Use the API evaluation to check extraction across complete documents.
What one call returns
Page one rendered with every block outlined, next to the JSON your code receives.
- Reading text layer
- Detecting layout
- Extracting tables
- Building JSON
Headings, paragraphs, tables and totals detected
Portsmouth, NH 03801
| Description | Qty | Unit | Amount |
|---|---|---|---|
| Oak countertop, 2.4 m | 2 | 640.00 | 1,280.00 |
| Cabinet doors, shaker | 12 | 85.00 | 1,020.00 |
| On site fitting | 1 | 450.00 | 450.00 |
Quote the invoice number with your transfer.
Goods remain ours until paid in full.
Pages 2 and later are parsed after you create an account.
{ "document": { "pages": 2, "parsed_pages": 1, "language": "en" }, "pages": [ { "number": 1, "blocks": [ { "type": "heading", "text": "Invoice", "bbox": [48, 52, 132, 84] }, { "type": "paragraph", "text": "Harbor Street Joinery, 14 Dock Lane, Portsmouth" }, { "type": "key_value", "pairs": { "Invoice no.": "INV-2026-0418", "Issued": "Oct 14, 2026", "Due": "Nov 13, 2026" } }, { "type": "table", "columns": ["Description", "Qty", "Unit", "Amount"], "rows": [ ["Oak countertop, 2.4 m", 2, 640.00, 1280.00], ["Cabinet doors, shaker", 12, 85.00, 1020.00], ["On site fitting", 1, 450.00, 450.00] ] }, { "type": "total", "label": "Total due", "value": 2983.75, "currency": "USD", "confidence": 0.98 } ] } ], "fields": { "invoice_number": { "value": "INV-2026-0418", "confidence": 0.99, "page": 1 }, "total": { "value": 2983.75, "confidence": 0.98, "page": 1 }, "due_date": { "value": "2026-11-13", "confidence": 0.97, "page": 1 } } }
Downloads from the demo include a watermark field and cover page one only.
Page one is parsed in your browser, so your file never reaches our servers.
One demo per day from this network. Create an account to parse more pages.
$ curl https://api.pdfparse.ai/v1/parse \ -H "Authorization: Bearer $PDFPARSE_API_KEY" \ -F file[email protected] \ -F outputs=json,markdown,csv
Mistral OCR and PdfParse side by side
Mistral OCR is an API model that reads a document and returns a page by page response. Each page carries Markdown, table content (inline, or separate as Markdown or HTML), image references, headers, footers and confidence scores, and an annotation option can return structured JSON that you define. PdfParse returns JSON, Markdown and CSV together and bills one page allowance.
| What matters | Mistral OCR | PdfParse |
|---|---|---|
| Core output | Markdown per page with tables and image placeholders | JSON, Markdown and CSV in one call |
| Tables | Inline Markdown or separate Markdown or HTML tables, which you convert to rows | Table extraction and CSV output on every plan |
| Structured fields | Document annotations with a schema you design and test | Growth includes up to 10 schemas with field confidence and source pages |
| Billing | Metered per 1,000 pages through the Mistral API, check the current rate before you compare | Monthly page allowance, scans at the same page price |
| Entry price | Pay as you go | Starter is $49 monthly or $24 per month billed yearly, with 2,000 pages |
| Delivery | API calls and batch processing | Python and Node SDKs, signed webhooks and batch jobs on Growth |
| Who it suits | Teams feeding page text to an LLM or search index | Developers who want results ready for their application |
Mistral details come from its public OCR documentation. Its price page lists OCR per 1,000 pages without a figure we could confirm on November 1, 2026, so we do not print a rate here. Look up your current rate before running the numbers.
Where the work moves
Mistral gives you clean Markdown quickly. What happens next is your code: splitting a Markdown table into rows, matching labels to fields, handling a total printed twice, flagging pages where a number is unclear. That is the part PdfParse is built around. Request JSON for the application, Markdown for a model prompt and CSV for the spreadsheet from the same call, then review low confidence fields against the source page.
What makes switching worth evaluating
Switching is worth testing when the code after the OCR step is larger than the OCR call.
- Skip the table parsing. CSV output means a table arrives as rows, not as Markdown you split yourself.
- Get fields, not just text. Growth schemas return named values with confidence and source pages.
- Keep one bill by pages. A fixed allowance is easier to budget than a metered rate when volumes swing.
- Use one call for three jobs. LLM context, database insert and finance export come from the same response.
How to evaluate a move from Mistral OCR
Test with the documents that cause your review queue today.
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1
Pick 20 real PDFs, including scans, multi page tables and the layouts your extraction code fails on most.
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2
Run them through your current Mistral pipeline and record how many need manual correction after your own post processing.
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3
Parse the same files with POST /v1/parse using the Python or Node SDK, requesting JSON, Markdown and CSV together.
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4
On Growth, create schemas through POST /v1/schemas for the fields you actually need and compare missing values, confidence and source pages.
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5
Count the post processing code you could delete, then choose an allowance that covers monthly pages.
Request three outputs in Python
Use the Python SDK to request the output bundle and print the CSV. Read the API key from your runtime environment.
The output request does not define a custom field schema. Create schemas separately through POST /v1/schemas on Growth or above.
import os
from pdfparse_ai import PdfParse
client = PdfParse(api_key=os.environ["PDFPARSE_API_KEY"])
result = client.parse("statement.pdf", outputs=["json", "markdown", "csv"])
print(result.csv)When Mistral OCR is the better pick
Mistral OCR is the better pick when you need page text and little else.
- You feed Markdown straight into an LLM or search index and do not need named fields or CSV.
- You process very large volumes of simple pages where a metered per page rate beats a monthly allowance.
- You already build on Mistral models and want OCR and generation under one vendor and key.
- You want to design your own annotation schema inside the same API as the model. PdfParse is a managed parser and not a general model platform.
Choose a plan for your monthly PDF volume
Every plan includes the three outputs. Schemas, signed webhooks and batch jobs start on Growth. Yearly prices are monthly equivalents of annual subscriptions.
| Plan | Yearly billing | Monthly billing | Pages per month | Fit |
|---|---|---|---|---|
| Starter | $24 per month | $49 per month | 2,000 | Standard outputs and scanned PDFs |
| Growth | $74 per month | $149 per month | 7,000 | Up to 10 schemas, webhooks and batch jobs |
| Scale | $249 per month | $499 per month | 24,000 | Unlimited schemas and zero retention mode |
| Enterprise | $749 per month | $1,499 per month | 72,000 | An EU or US processing region |
When the allowance runs out, parsing pauses without automatic overage charges. More pages require a higher plan. Unused pages do not roll over.
- Starter 2,000 pages, 1 API key, 1 seat $49 per month $24 per month, $288 billed yearly
- Growth 7,000 pages, 5 API keys, 3 seats $149 per month $74 per month, $888 billed yearly
- Scale 24,000 pages, 20 API keys, 10 seats $499 per month $249 per month, $2,988 billed yearly
- Enterprise 72,000 pages, unlimited API keys with per key limits, 25 seats $1,499 per month $749 per month, $8,988 billed yearly
FAQ
What is the best alternative to Mistral OCR
PdfParse is a strong alternative for developers who need fields, CSV tables and JSON from PDFs rather than only Markdown. Mistral OCR stays the better choice for raw page text at high volume or when you already build on Mistral models.
Is Mistral OCR good for invoices and tables
Mistral OCR reads tables and returns them as Markdown or HTML, and annotations can return structured JSON. You design and test the schema and convert tables into rows yourself. PdfParse returns CSV tables and, on Growth, schema fields with confidence and source pages.
How much does Mistral OCR cost
Mistral meters OCR per 1,000 pages through its API and states batch processing lowers prices for high volume work. Rates change, so confirm the current figure on Mistral's pricing page. PdfParse starts at $49 monthly for 2,000 pages, or $24 per month billed yearly.
Is PdfParse cheaper than Mistral OCR
For plain OCR at high volume, probably not, because a metered per page rate is hard to beat. PdfParse is worth testing when field extraction and table conversion code costs your team more than the OCR itself.
Test your workflow with your own PDF
Try page one in your browser without a card. Compare fields, text and tables, then evaluate the API against your volume and workflow requirements.