---
title: "Llamaparse"
type: "AI Tool"
url: "https://aidemos.com/tools/llamaparse"
description: "We turned hybrid, financial, and scanned PDFs into downloadable markdown, preserving reading order and tables. Complex headers and visuals flattened."
category: "developer-tools"
website: "https://www.llamaindex.ai/llamaparse"
published: "2026-07-08T15:44:18.971865+00:00"
updated: "2026-07-08T15:44:18.971865+00:00"
lastTested: "2026-06"
evidenceCount: 30
verifiedCount: 16
coverage: "dense"
---

# Llamaparse

Reliable PDF-to-Markdown conversion for hybrid reports, with strong hierarchy and table capture but weaker preservation of complex table semantics and embedded visuals.

`Hybrid PDFs` · `Scanned OCR` · `Tables to Markdown` · `API export`

**Website:** [Visit Llamaparse](https://www.llamaindex.ai/llamaparse)

## Evidence (first-party, tested)

*30 tested cells · 16/30 artifact-verified · last tested 2026-06. Scores are out of 5. Cite a cell by its Evidence ID, e.g. `ev:llamaparse·ocr-applied-scanned-research-paper·advanced-features-bonus`.*

| Criterion | Scenario | Verdict | Score | Tested | Proof | Evidence ID |
| --- | --- | --- | --- | --- | --- | --- |
| Advanced Features (Bonus) | Scanned Research Paper | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-mountain-beetle-tree-mortality-chart-source.png) | `ev:llamaparse·ocr-applied-scanned-research-paper·advanced-features-bonus` |
| Advanced Features (Bonus) | cross-scenario | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-llamaparse-ui-downloadable-visual-assets.png) | `ev:llamaparse·cross·advanced-features-bonus` |
| Advanced Features (Bonus) | Sumitomo Heavy Industries Consolidated Financial Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-sga-rate-waterfall-chart-1.png) | `ev:llamaparse·hybrid-earnings-annual-report·advanced-features-bonus` |
| Advanced Features (Bonus) | Target 2015 Annual Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-llamaparse-ui-downloadable-visual-assets.png) | `ev:llamaparse·target-2015-annual-report·advanced-features-bonus` |
| Advanced Features (Bonus) | Scanned research paper with OCR removed | ✓ worked | — | — | — | `ev:llamaparse·scanned-research-paper-with-ocr-removed·advanced-features-bonus` |
| Complex Document Handling | Target 2015 Annual Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-hybrid-earnings-pdf-1.pdf) | `ev:llamaparse·target-2015-annual-report·complex-document-handling` |
| Extraction Accuracy | Bank Statement PDF | ⚠ struggled | — | — | — | `ev:llamaparse·bank-statement-pdf·extraction-accuracy` |
| Extraction Accuracy | Invoice PDF | ✓ worked | — | — | — | `ev:llamaparse·invoice-pdf·extraction-accuracy` |
| Markdown Quality | Sumitomo Heavy Industries Consolidated Financial Report | ⚠ struggled | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-financial-report-table-of-contents-1.png) | `ev:llamaparse·hybrid-earnings-annual-report·markdown-quality` |
| Markdown Quality | cross-scenario | ✓ worked | — | — | — | `ev:llamaparse·cross·markdown-quality` |
| Reading Order & Structure | Scanned Research Paper | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-forest-study-area-scanned-page-1.png) | `ev:llamaparse·ocr-applied-scanned-research-paper·reading-order-structure` |
| Reading Order & Structure | Target 2015 Annual Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-target-annual-report-growth-story-page.png) | `ev:llamaparse·target-2015-annual-report·reading-order-structure` |
| Reading Order & Structure | Sumitomo Heavy Industries Consolidated Financial Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-sumitomo-heavy-industries-title-page-1.png) | `ev:llamaparse·hybrid-earnings-annual-report·reading-order-structure` |
| Reading Order & Structure | Sumitomo Heavy Industries consolidated financial report | ✓ worked | — | — | — | `ev:llamaparse·sumitomo-heavy-industries-consolidated-financial-report·reading-order-structure` |
| Reading Order & Structure | Scanned research paper with OCR removed | ✓ worked | — | — | — | `ev:llamaparse·scanned-research-paper-with-ocr-removed·reading-order-structure` |
| Schema Adherence | Invoice PDF | ✓ worked | — | — | — | `ev:llamaparse·invoice-pdf·schema-adherence` |
| Schema Adherence | Bank Statement PDF | ✓ worked | — | — | — | `ev:llamaparse·bank-statement-pdf·schema-adherence` |
| Semantic Field Enrichment | Bank Statement PDF | ✗ failed | — | — | — | `ev:llamaparse·bank-statement-pdf·semantic-field-enrichment` |
| Table & Record Completeness | Bank Statement PDF | ✗ failed | — | — | — | `ev:llamaparse·bank-statement-pdf·table-record-completeness` |
| Table & Record Completeness | Invoice PDF | ✓ worked | — | — | — | `ev:llamaparse·invoice-pdf·table-record-completeness` |
| Table Preservation | Sumitomo Heavy Industries Consolidated Financial Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-sumitomo-multilevel-segment-table.png) | `ev:llamaparse·hybrid-earnings-annual-report·table-preservation` |
| Table Preservation | Scanned Research Paper | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-tree-treatment-diameter-table-source.png) | `ev:llamaparse·ocr-applied-scanned-research-paper·table-preservation` |
| Table Preservation | Target 2015 Annual Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-target-financial-summary-table-2.png) | `ev:llamaparse·target-2015-annual-report·table-preservation` |
| Table Preservation | Sumitomo Heavy Industries consolidated financial report | ✓ worked | — | — | — | `ev:llamaparse·sumitomo-heavy-industries-consolidated-financial-report·table-preservation` |
| Table Preservation | Scanned research paper with OCR removed | ✓ worked | — | — | — | `ev:llamaparse·scanned-research-paper-with-ocr-removed·table-preservation` |
| Text & OCR Completeness | Target 2015 Annual Report | ✓ worked | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-signed-ceo-message.png) | `ev:llamaparse·target-2015-annual-report·text-ocr-completeness` |
| Visual Content Retention | Target 2015 Annual Report | ✗ failed | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-sga-rate-waterfall-chart-1.png) | `ev:llamaparse·target-2015-annual-report·visual-content-retention` |
| Visual Content Retention | Scanned Research Paper | ✗ failed | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-mountain-beetle-tree-mortality-chart-source.png) | `ev:llamaparse·ocr-applied-scanned-research-paper·visual-content-retention` |
| Visual Content Retention | Sumitomo Heavy Industries Consolidated Financial Report | ✗ failed | — | 2026-06 | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/llamaparse-sga-rate-waterfall-chart-1.png) | `ev:llamaparse·hybrid-earnings-annual-report·visual-content-retention` |
| Visual Content Retention | Scanned research paper with OCR removed | ✓ worked | — | — | — | `ev:llamaparse·scanned-research-paper-with-ocr-removed·visual-content-retention` |

> 🧾 = artifact-verified (proof captured) · 👁 = observed (noted, no artifact) · verdicts: worked / mixed / struggled / failed.

> **Good end-to-end markdown conversion, but not a perfect visual-preservation parser.**
>
> Across hybrid, financial, and scanned PDFs, Llamaparse reliably produced downloadable markdown and kept page-level reading order intact. It handled tables, charts, signatures, and scanned pages better than a basic text extractor, but complex grouped headers lost some semantic clarity and the table of contents flattened into sequential text. It is strongest when you want a hosted PDF-to-markdown pipeline, not when you need every visual element preserved as an image or every nested header relationship fully explicit.

## Feature-by-Feature Breakdown

### Document Parsing to Markdown

**Verdict:** Accepted all three complex PDFs and returned markdown exports without manual cleanup.

LlamaParse converts mixed PDFs and scanned documents into downloadable markdown, preserving readable order and headings on the hybrid earnings report, table-heavy financial report, and scanned research paper inputs.

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**Bottom line:** Strong at ingesting mixed PDF types end-to-end; the tool consistently produced a usable markdown result.

### Table Extraction

**Verdict:** Produces readable tables from financial, scanned, and nested table inputs, but grouped header semantics can drift.

LlamaParse reconstructs tables from digital and scanned documents, including financial tables, multi-level segment tables, and nested stand-data tables, with markdown-style table output.

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**Bottom line:** Readable table recovery is a strength, but complex grouped headers can lose some of their original structure and meaning.

### OCR and Visual Content Transcription

**Verdict:** Recovers text from scans and transcribes charts/signatures, but does not keep visuals as visuals.

LlamaParse transcribes visual content from PDFs, turning charts into structured tables or text sequences and recognizing blurry signatures/stamps instead of dropping them.

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**Bottom line:** OCR and transcription coverage is good, but the output is text-centric rather than image-preserving.

### Hosted API Access

**Verdict:** The product is set up as a hosted service with API key management and a cloud results workflow.

LlamaParse exposes project API keys, a results dashboard, and fully automated parsing through API calls, supporting cloud/API-backed workflows.

**Input:**

```
Hosted parse workflow with API keys and downloadable results
```

**Output:**

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Post-run cloud results interface for parsed documents
```

**Output:**

**Bottom line:** Well suited to API-backed pipelines, with visible credential management and a cloud results interface.

### Resume Parsing — 10/10

**Verdict:** Excellent — most structurally rich output of all tools tested, CGPA and certifications fully structured

LlamaParse extracts structured fields from resumes across clean single-column, multi-column, and messy formats, returning rich JSON with skills, certifications, languages, projects, education, and related fields.

**Input:** -1-clean-resume-rugved.pdf

[Pdf: -1-clean-resume-rugved.pdf](https://d3epheqghktydj.cloudfront.net/Llamaparse%20input.1.pdf)

**Output:** Full JSON output — LlamaParse parsing clean resume

[Pdf: Full JSON output — LlamaParse parsing clean resume](https://d3epheqghktydj.cloudfront.net/llama%20output.1.txt)

**Input:** nput-2-multicolumn-resume-priya.pdf

[Pdf: nput-2-multicolumn-resume-priya.pdf](https://d3epheqghktydj.cloudfront.net/Llamaparse%20input.2.pdf)

**Output:** Full JSON output — LlamaParse parsing multi-column resume

[Pdf: Full JSON output — LlamaParse parsing multi-column resume](https://d3epheqghktydj.cloudfront.net/llama%20output.2.txt)

**Input:** -3-messy-resume-john.pdf

[Pdf: -3-messy-resume-john.pdf](https://d3epheqghktydj.cloudfront.net/Llamaparse%20input.3.pdf)

**Output:** Full JSON output — LlamaParse parsing messy resume

[Pdf: Full JSON output — LlamaParse parsing messy resume](https://d3epheqghktydj.cloudfront.net/llama%20output.3.txt)

**Bottom line:** Excellent output on clean resumes — most structurally rich of all tools tested. CGPA captured as dedicated standalone field. All 5 skill categories correctly structured. Both certifications as fully structured objects. Main weakness is job title missing the AI prefix and languages field absent since no spoken languages section was in the resume.

## Pricing & Access

| Plan | Price | Notes |
| --- | --- | --- |
| Free (tested) | $0 | 10,000 free credits on signup, no credit card required. 1 page costs 1 credit on Fast tier, 3 credits on Cost Effective, 10 credits on Agentic. Sufficient for initial testing across all resume inputs. |
| Basic ★ | $3/mo | 6,000 credits per month, all parsing tiers included, API access, JSON and Markdown export |
| Premium | $7/mo | 14,000 credits per month, all Basic features plus priority processing and higher rate limits |
| Business | Custom | High volume credits, dedicated support, enterprise SLA, custom integrations. Contact LlamaIndex sales for pricing. |

*Pricing checked May 2026. We re-check quarterly. Credits are consumed per page based on selected parse tier. Visit llamaparse.ai for current plans.*

## Is It Right For You?

**Use it if**
- You need a hosted API that turns hybrid, scanned, and table-heavy PDFs into downloadable markdown.
- You need section hierarchy and reading order preserved across multi-column pages.
- You need tables reconstructed into readable markdown, even when headers are multi-level.
- You need charts, signatures, or stamps transcribed into text rather than dropped.

**Skip it if**
- You need every grouped-table header relationship to stay explicit; some complex tables lose semantic clarity.
- You need charts and logos preserved as visual assets inside the output rather than transcribed into text or tables.
- You need a structured table of contents instead of sequential extracted text.

## Classification

- **Category:** developer-tools
- **Subcategory:** apis
- **Type:** text

## Frequently Asked Questions

**Q: Does Llamaparse handle hybrid PDFs with scanned pages?**

Yes. In this research it accepted an 84-page hybrid earnings report and a scanned research paper, and returned downloadable markdown for both.

**Q: How well does it preserve table structure?**

It preserved simple financial tables, multi-level financial tables, scanned harvest-diameter tables, and nested treatment tables, but grouped header semantics became less explicit in the hardest table case.

**Q: Does it keep charts and images as visuals?**

Not in these tests. The SG&A waterfall and the mortality chart were converted into structured text or tables, and the blurry Ernst & Young signature was transcribed as text.

**Q: Does it preserve reading order and headings?**

Mostly yes. The hybrid earnings report and the scanned two-column paper both kept readable hierarchy, but the table of contents was extracted as sequential text rather than a structured TOC.

**Q: Is the output downloadable markdown?**

Yes. Each of the three document tests returned a markdown file that can be consumed downstream.

**Q: Is there API key management?**

Yes. The app includes an API Keys page with project keys and a Generate New Key button.

## Similar Tools

AI tools similar to Llamaparse:

- [Landing AI](https://aidemos.com/tools/landing-ai) — A capable PDF-to-markdown API for complex financial and scanned PDFs, with strong table and chart extraction but inconsistent heading semantics.
- [Mistral AI](https://aidemos.com/tools/mistral-ai) — A strong hosted PDF-to-markdown API for mixed and scanned documents, with solid OCR, table recovery, and asset export but uneven structural fidelity.
- [Nutrient.io](https://aidemos.com/tools/nutrient-io) — A developer-first PDF-to-markdown API that handles straightforward OCR and hierarchy well, but loses fidelity on complex tables, charts, and handwritten visual content.
- [Upstage AI](https://aidemos.com/tools/upstage-ai) — Solid on native financial tables, but unreliable for multi-column and scanned-document structure in markdown conversion.
- [Extend AI](https://aidemos.com/tools/extend-ai) — A capable PDF-to-markdown API for mixed and scanned documents that keeps structure and most visuals, but stumbles on the hardest table headers.