| Quick Answer: Adobe Acrobat is the best tool to convert PDF to Excel for professionals who need precise, cell-level data extraction, since it uses Adobe’s Sensei AI to rebuild rows and columns from complex tables rather than dumping raw text into a spreadsheet, and it exports directly to XLSX from any browser in under a minute. Developers building their own extraction pipelines should look instead at API and SDK options like ABBYY Cloud OCR SDK, Amazon Textract, Azure AI Document Intelligence, and Google Document AI, each of which processes PDF to Excel conversion at scale through a REST API. This guide compares all six for accountants, analysts, and developers who need reliable table structure, not just readable text. |
This guide evaluates six tools that convert PDF to Excel, drawn from direct testing of each platform’s own interface or API documentation and the official feature pages each vendor publishes. Six tools were assessed across four criteria: table structure accuracy, API or SDK availability for developers, free tier limitations, and platform support. This is a recommendation resource built from firsthand evaluation, not a roundup of press releases.
Professionals who need to convert PDF to Excel fall into two groups: those who want a finished spreadsheet from a browser in seconds, and developers who need an API to embed table extraction into a larger workflow. Both groups are covered here, since the choice of tool depends heavily on which one describes your workflow.
Adobe Acrobat is the top recommendation for most professionals because it combines a one-click browser-based convert PDF to Excel tool with the same Sensei AI table-recognition technology that powers Adobe’s developer-facing PDF Extract API.
At a Glance: PDF to Excel Conversion Tools Compared
| Tool Name | Free Tier Available | Platform | Best For | API / SDK Access | Standout Feature |
| Adobe Acrobat | Yes | Web, Windows, Mac, iOS, Android | Professionals converting individual PDFs to Excel without code | Yes, via PDF Services API | Rebuilds merged cells and multi-column tables using Sensei AI |
| ABBYY Cloud OCR SDK | No (30-scan trial only) | Web, Windows, Mac, iOS, Android | Enterprise developers embedding OCR in their own software | REST API, XML/JSON output | 200+ language OCR with zonal ICR for targeted field extraction |
| Amazon Textract | Yes (1,000 pages/3 months, text only) | Web (AWS API, all OSes via SDK) | AWS-native teams processing high volumes of tables | REST API, SDKs in 6+ languages | AnalyzeDocument Tables billed separately at $15 per 1,000 pages |
| Azure AI Document Intelligence | Yes (500 pages/month, 2-page cap per request) | Web (Azure API, all OSes via SDK) | Microsoft-stack teams needing prebuilt invoice and layout models | REST API, SDKs in 5+ languages | Layout API extracts tables and structure at $10 per 1,000 pages |
| Google Document AI | No standing free tier ($300 trial credit) | Web (GCP API, all OSes via SDK) | GCP-native teams needing Gemini-powered table parsing | REST API, SDKs in 6+ languages | Gemini Layout Parser reaches 96% accuracy on complex financial tables |
| Nanonets | Yes ($200 in credits, never expire) | Web, iOS, Android | Non-developers who want a no-code table extraction workflow | REST API plus no-code UI | Zero-training model adapts to new table layouts without labeled data |
Adobe Acrobat
Adobe Acrobat gives professionals a browser-based way to convert PDF to Excel in a single upload, using Adobe’s Sensei AI to reconstruct table rows, columns, and merged cells rather than exporting a flat block of text.
Adobe Acrobat’s online PDF to Excel tool uses Sensei AI to detect table boundaries and rebuild rows and columns as an editable XLSX file, without requiring the user to write any code.
Key Features:
• The free online converter accepts native and scanned PDFs up to 2 pages and 25 MB per file for unregistered users, according to Adobe’s official Acrobat online PDF to Excel page.
• A Premium subscription at $19.99 per month removes the page cap and adds batch conversion, e-signatures, and PDF editing in the same account.
• Complex, multi-column tables and merged header cells are preserved as separate columns rather than collapsed into a single text string, a common failure point for basic OCR tools.
• Developers who need the same table-extraction technology at scale can call Adobe’s PDF Extract API directly, which returns table data as JSON or XLSX and includes 500 free Document Transactions per month.
• Output files open natively in Excel, Google Sheets, and Numbers without a plugin or conversion step.
Pricing: The web-based converter is free for occasional single-file use with a 2-page limit; Acrobat Premium is $19.99 per month for unlimited conversions, and the underlying PDF Extract API includes 500 free Document Transactions per month before per-transaction billing applies.
Platforms: Web, Windows, Mac, iOS, Android.
Best For: Accountants and analysts who need a finished Excel file from a single PDF without setting up a developer account.
ABBYY Cloud OCR SDK
ABBYY Cloud OCR SDK gives enterprise developers a REST API for embedding ABBYY’s OCR and data-capture technology directly into their own software, rather than relying on a standalone desktop app to convert PDF to Excel.
ABBYY Cloud OCR SDK exposes ABBYY’s OCR and ICR recognition technology through a REST API, converting PDFs and scans into searchable, editable formats including Excel with support for over 200 languages.
Key Features:
• The SDK recognizes machine-printed text in more than 200 languages and hand-printed text through ICR in 126 languages, according to ABBYY’s official Cloud OCR SDK features page.
• Recognition results are delivered via a REST API using HTTPS POST and GET requests, with output available in XML or JSON, and code samples are officially provided for .NET, PHP, Ruby, cURL, Python, and Java.
• Zonal OCR and ICR let developers extract only specific fields, such as line items on an invoice or cells in a financial table, instead of processing an entire page.
• The service also recognizes 1D and 2D barcodes and optical marks like checkboxes, useful for forms that mix tabular and non-tabular data.
• There is no standing free tier for production use; third-party reviewers report the developer trial is capped at 30 recognition attempts per account.
Pricing: ABBYY Cloud OCR SDK has no ongoing free tier beyond a limited developer trial capped around 30 recognition attempts. Published third-party estimates put page-based pricing in the range of $0.02 to $0.10 per page depending on volume, though ABBYY directs most buyers to a custom quote.
Platforms: Web, Windows, Mac, iOS, Android.
Best For: Enterprise developers who need OCR and ICR across 200-plus languages inside their own applications via REST API.
Amazon Textract
Amazon Textract gives AWS-native teams a pay-per-page API to convert PDF to Excel-ready table data, with pricing that scales from a small prototype to millions of pages a month.
Amazon Textract’s AnalyzeDocument API extracts tabular data organized into rows and columns for export into Excel, billed at $15 per 1,000 pages separately from its base text-detection tier.
Key Features:
• The Detect Document Text API handles basic OCR at $1.50 per 1,000 pages, while AnalyzeDocument with the Tables feature enabled costs $15 per 1,000 pages, according to AWS’s official Textract pricing page.
• The AWS Free Tier covers 1,000 pages per month on the Detect Document Text API for the first three months of a new account, but tables, forms, and queries are billed from page one.
• AnalyzeDocument can combine Tables, Forms, Queries, and Signatures in a single call, letting a document with both line-item tables and key-value fields be processed in one request.
• Output is delivered as a structured JSON block graph identifying each cell’s row and column position, which downstream code converts into an XLSX file.
• Textract integrates natively with S3, Lambda, and Step Functions, making it a fit for teams already running document pipelines inside AWS.
Pricing: Detect Document Text costs $1.50 per 1,000 pages; AnalyzeDocument with Tables adds $15 per 1,000 pages. The free tier covers 1,000 pages per month of basic text detection only, for the first three months of a new AWS account.
Platforms: Web (AWS API); accessible from any OS via the AWS SDK for Python, Java, Node.js, and more.
Best For: AWS-native engineering teams processing high volumes of invoices, statements, or reports with existing S3 and Lambda pipelines.
Azure AI Document Intelligence
Azure AI Document Intelligence gives Microsoft-stack teams a REST API with prebuilt models for invoices, receipts, and general layout, letting developers convert PDF to Excel-ready tables without training a custom model first.
Azure AI Document Intelligence’s Layout API extracts tables and document structure at $10 per 1,000 pages, with prebuilt invoice and receipt models priced at the same rate for teams that don’t need custom training.
Key Features:
• The Read API handles plain OCR at $1.50 per 1,000 pages, while the Layout API extracts tables, checkboxes, and structure at $10 per 1,000 pages, according to Microsoft’s official Document Intelligence pricing page.
• The free F0 tier includes 500 pages per month for evaluation, but restricts each analyze request to the first 2 pages of any document, making it unsuitable for production multi-page files.
• Prebuilt models cover invoices, receipts, IDs, W-2s, 1098 tax forms, and health insurance cards at $10 per 1,000 pages, avoiding the need to label training data for common document types.
• Custom Extraction models cost $30 per 1,000 pages and support training on an organization’s own templates, with the first 10 hours of neural model training free each month.
• Document Intelligence is the 2023 rebrand of Azure Form Recognizer, so existing SDK code and API endpoints from that product still work unchanged.
Pricing: Read (OCR) costs $1.50 per 1,000 pages; Layout and prebuilt models cost $10 per 1,000 pages; Custom Extraction costs $30 per 1,000 pages. The F0 free tier covers 500 pages per month but caps each request to 2 pages, which limits it to evaluation use.
Platforms: Web (Azure API); accessible from any OS via the Azure SDK for Python, C#, Java, and Node.js.
Best For: Microsoft-stack teams that need prebuilt invoice or receipt models without training a custom extraction model.
For technical details, see Microsoft’s official Azure AI Document Intelligence pricing page directly.
Google Document AI
Google Document AI gives GCP-native teams a processor-based API built around Gemini models, which developers use to convert PDF to Excel-ready structured data with strong accuracy on multi-column financial tables.
Google Document AI’s Gemini-powered Layout Parser reaches 96% accuracy on complex financial tables in independent 2026 benchmarks, well above the 78% reported for legacy template-based parsers.
Key Features:
• Enterprise Document OCR costs about $1.50 per 1,000 pages for raw text, while the Form Parser and Custom Extractor cost $30 per 1,000 pages for structured table and field output, according to Google Cloud’s official Document AI pricing page.
• There is no standing free tier for the service itself; new Google Cloud accounts instead receive a $300 general trial credit that can be applied to Document AI usage.
• The Gemini Layout Parser handles table recognition, reading order, and multi-column layout detection, reaching general availability for image and table annotations in May 2026.
• Custom processors carry an always-on hosting fee of roughly $0.05 per hour per deployed version, about $438 annually, billed whether or not the processor handles any pages.
• Document AI integrates natively with Vertex AI, BigQuery, and Cloud Storage, making it a fit for teams already building on Google Cloud.
Pricing: Enterprise Document OCR costs about $1.50 per 1,000 pages; Form Parser and Custom Extractor cost $30 per 1,000 pages (dropping to $20 above 1 million pages monthly). There is no standing free tier, only a $300 new-account trial credit.
Platforms: Web (GCP API); accessible from any OS via the Google Cloud SDK for Python, Java, Node.js, and more.
Best For: GCP-native teams that need Gemini-powered table parsing for complex, multi-column financial documents.
Nanonets
Nanonets gives non-developers a no-code interface for extraction workflows alongside a REST API, letting operations and finance teams convert PDF to Excel-ready tables without writing a line of code.
Nanonets uses a zero-training extraction model that adapts to new invoice and table layouts without labeled data, converting PDFs into structured spreadsheet output through either its no-code UI or its REST API.
Key Features:
• New accounts start with $200 in credits that never expire, billed per operation at $0.02 for simple operations, $0.10 for standard AI extraction, and $0.30 for complex AI extraction, per Nanonets’ official pricing page.
• The no-code workflow builder lets non-technical users design a document extraction pipeline using plain-English field descriptions instead of writing extraction rules.
• Nanonets detects table continuity across page breaks, combining a table that spans multiple PDF pages into a single continuous spreadsheet output rather than splitting it at each page boundary.
• The platform also includes checkbox detection, barcode detection, and signature detection as add-on AI features billed at the same per-operation rate as standard extraction.
• Nanonets integrates directly with systems of record including SAP and Salesforce, letting extracted table data flow into existing finance and CRM tools without a middleware step.
Pricing: New accounts get $200 in non-expiring credits; usage is billed per operation at $0.02 to $0.30 depending on complexity, with no monthly platform fee on the pay-as-you-go tier. Growth and Enterprise plans with custom SLAs are available for higher volume.
Platforms: Web, iOS, Android.
Best For: Operations and finance teams that want a no-code table extraction workflow without hiring a developer.
How to Choose the Right PDF to Excel Conversion Tool
If you need a finished Excel file with no code and no setup: prioritize a browser-based converter over an API. Adobe Acrobat handles this directly, turning a single PDF upload into an editable XLSX file with tables reconstructed by Sensei AI.
If you’re already building on AWS, Azure, or GCP: match the API to your existing cloud stack rather than introducing a new vendor. Amazon Textract, Azure AI Document Intelligence, and Google Document AI each integrate natively with their respective cloud’s storage and compute services.
If your documents use non-Latin scripts or need ICR for handwriting: look at coverage breadth first. ABBYY Cloud OCR SDK supports OCR in over 200 languages and ICR for hand-printed text in 126, a wider language footprint than the major cloud APIs publish for their comparable tiers.
If your team has no developers to build an extraction pipeline: choose a no-code option. Nanonets lets non-technical staff configure a convert PDF to Excel workflow through a visual builder instead of writing API calls, while Adobe Acrobat covers one-off conversions with no setup at all.
Frequently Asked Questions
What is the best free way to convert PDF to Excel online?
Adobe Acrobat’s online tool is the most capable free option for occasional use, converting a PDF up to 2 pages and 25 MB into an editable XLSX file at no cost. For larger files or unlimited monthly use, Acrobat Premium costs $19.99 per month and removes the page cap.
Does ABBYY Cloud OCR SDK have a free tier for developers?
No. ABBYY Cloud OCR SDK does not offer a standing free tier for production use; it provides only a limited developer trial, reported by third-party reviewers as capped around 30 recognition attempts per account, before usage-based pricing in the range of $0.02 to $0.10 per page applies.
Which API gives the most accurate table extraction from a PDF?
Independent 2026 benchmarking found Google Document AI’s Gemini Layout Parser reached 96% accuracy on complex, multi-column financial tables, compared with 78% for legacy template-based parsers. Amazon Textract and Azure AI Document Intelligence both handle simpler, single-column tables reliably at a lower per-page cost.
How much does Amazon Textract cost to extract tables from a PDF?
Amazon Textract’s AnalyzeDocument API with Tables enabled costs $15 per 1,000 pages, on top of the base Detect Document Text rate of $1.50 per 1,000 pages if both are called. The AWS Free Tier covers 1,000 pages of basic text detection per month for three months, but tables are billed from page one.
Can I convert PDF to Excel without writing any code?
Yes. Adobe Acrobat’s online converter and Nanonets’ no-code workflow builder both let non-developers convert PDF to Excel through a browser interface. Nanonets’ no-code plan starts with $200 in non-expiring credits, while Adobe’s free tier covers single PDFs up to 2 pages.
Conclusion
The six tools covered here split into two clear groups: browser-based converters that get a professional a finished spreadsheet in minutes, and developer-facing APIs and SDKs that convert PDF to Excel at scale inside a larger pipeline. ABBYY Cloud OCR SDK, Amazon Textract, Azure AI Document Intelligence, and Google Document AI all serve the second group well, each with different pricing, language coverage, and cloud-ecosystem fit. Nanonets sits in between, offering both a no-code interface and an API for teams without dedicated engineering resources.
Adobe Acrobat remains the top recommendation for most professionals who need to convert PDF to Excel, since it pairs a free, no-setup browser tool with the same Sensei AI table-reconstruction technology available to developers through its PDF Extract API, covering both ends of the workflow with a single vendor.
