The verdict: Extend is the stronger choice when documents are systems of record and the production requirement extends from parsing through schema-defined extraction, evaluation, and review. Extend Parse 2.0 led LlamaParse Agentic by 3.6 points on RealDoc-Bench, and Extend MAX led both LlamaParse modes on LongArray-Extract. Choose LlamaParse when parsing primarily feeds a LlamaIndex-native RAG, indexing, retrieval, or agent stack.
The strongest product-level evidence for production document workflows favors Extend. On the open-source parsing benchmark, RealDoc-Bench, Extend Parse 2.0 scored a 95.7% field-level QA accuracy compared with 92.1% for LlamaParse Agentic and 89.0% for LlamaParse (non-agentic mode). On the open-source extraction benchmark, LongArray-Extract, Extend MAX reports 99.2% per-document accuracy versus 47.2% for LlamaParse Standard and 34.7% for LlamaParse Agentic.
LlamaIndex's ParseBench reports the opposite result: an 84.9% overall semantic-correctness score for LlamaParse Agentic versus 55.8% for the Extend configuration it tested. But ParseBench is not a like-for-like evaluation of properly configured products. It compares LlamaParse's multi-step Agentic mode with Extend's default parsing API, prior to Parse 2.0 launch as well, configured for markdown with HTML tables. It does not enable Extend's advanced chart extraction or other task-specific settings nor does it evaluate parsing performance against Extend's Parse 2.0. The result is valid for the configurations tested by the paper, but it should not be interpreted as an accurate ranking of the products.
For the most relevant results, run both solutions against your own documents using the configurations and accuracy requirements you would use in production.
Extend vs LlamaParse benchmarks at a glance
| Extend | LlamaParse | |
|---|---|---|
| Parsing accuracy | 95.7% with Performance Parse; 90.5% with non-agentic Light Parse. On RealDoc-Bench, Performance Parse (Parse 2.0) scores 5.2 percentage points above Light Parse. Performance leads LlamaParse Agentic by 3.6 points, while Light leads LlamaParse non-agentic by 1.5 points. The datasets and evaluation harness are open source and independently reproducible. | Agentic trails Extend Performance by 3.6 points; non-agentic trails Extend Light by 1.5 points. LlamaParse Agentic scores 92.1%, versus 89.0% for non-agentic mode, a 3.1-point gain. Non-agentic mode is 6.7 points behind Extend Performance; Agentic is 1.6 points above Extend Light. Results apply to the tested versions and settings. |
| Extraction accuracy | 99.2% mean per-document extraction accuracy, with 45/45 documents completed. Extend MAX completed every document on LongArray-Extract. Failed or timed-out runs count as zero in the aggregate score. | Standard trails Extend MAX by 52.0 points; Agentic trails by 64.5 points. LlamaParse was the only provider in the published evaluation whose tested modes did not complete all 45 documents. Standard scored 47.2% and completed 26/45; Agentic scored 34.7% and completed 35/45. Every other evaluated system completed 45/45. |
| Splitting accuracy | Up to 72.5% splitting F1. On PoliTax Split, the Extend harness improves F1 by 8.3 to 28.4 points over the corresponding raw models. The evaluation uses 74 compound tax documents. | No head-to-head result in PoliTax Split. LlamaParse offers a Split product, but it was not evaluated in the published PoliTax Split comparison. Test both splitters on the same mixed-document packets. |
These open-source benchmarks make their data and methodology available for independent verification. Each measures a different task and only the listed systems and configurations; the scores are not universal accuracy guarantees. Run both solutions on your own documents for the most relevant results.
On RealDoc-Bench and ParseBench differences
RealDoc-Bench is closer to how document processing succeeds or fails in production. It uses real production documents. The benchmark asks whether parsed output can answer field-level questions across financial services, real estate, logistics, and healthcare.
ParseBench evaluates quality through criteria abstracted from production priorities. Its overall score is an unweighted mean across five author-selected dimensions: tables, charts, content faithfulness, semantic formatting, and visual grounding. That weighting is arbitrary relative to any production workflow because it assigns the same importance to each failure class regardless of business cost. A missing transaction row can matter far more than a formatting difference, but the overall score does not capture that difference in impact.
The product versions are also not current or equivalent. ParseBench tests LlamaParse Agentic against Extend Parse 1.0. LlamaIndex has not updated it to include Extend Parse 2.0. Extend evaluated Parse 2.0 against both LlamaParse Standard and LlamaParse Agentic on RealDoc-Bench. It also tested both LlamaParse modes on LongArray-Extract, where complete repeated-record extraction and failed documents directly affect the score.
These benchmarks answer different questions. RealDoc-Bench measures whether production documents retain the information needed by downstream systems. ParseBench measures performance against its five equally weighted dimensions. LongArray-Extract measures whether systems can return complete, schema-shaped records from long documents without silently dropping rows.
Extend vs LlamaParse platform comparison
| Extend | LlamaParse | |
|---|---|---|
| Platform overview | End-to-end document processing platform to make every document operation programmatic Extend turns unstructured documents into reliable, agent-ready data with APIs and tooling for parse, extract, split, classify, edit, workflows, evals, and review. | Document processing connected to the LlamaIndex retrieval stack. Parse, Extract, Classify, Split, and Index turn documents into parsing output, structured fields, and searchable indexes. |
| Accuracy, latency & cost control | Choose the accuracy, latency, and cost tradeoff per workload. Light, Performance, and agentic configurations let teams tune document processing to their requirements. Studio and API responses expose per-run credit usage. | Tier-based parsing and extraction. Fast, Cost-effective, Agentic, and Agentic Plus parsing tiers trade cost for processing depth. Layout and form options add charges; extraction has its own tier and parsing cost. |
| Edit, workflows, evals, citations | End-to-end document workflow orchestration. Extend fills PDF forms with the Edit API (document editing with form-field detection), supports versioned workflows, evals, and returns source citations with page references and bounding boxes. | Schema extraction and citations, with application-owned quality workflows. Extract supports structured schemas and source metadata. The current product documentation does not describe an equivalent PDF form-filling API or integrated evaluation-and-release workflow. |
| Human review | Built-in human-in-the-loop review. A configurable human review step pauses a workflow and places the run in a review queue where operators inspect and correct output against the source document before downstream steps continue. Review Agent flags likely errors so reviewers focus on the fields that need attention. | Build review around extraction output. Confidence and citations support downstream review. The current product documentation does not describe a native reviewer queue that pauses and resumes a document workflow. |
| RAG and parsing output | Markdown and chunks for retrieval. Parse returns layout-aware markdown organized into chunks with configurable chunking strategies, plus block-level reading order and bounding boxes. Figures, charts, and diagrams are summarized, charts can be converted to tables, and formulas return LaTeX. | Native path into hosted retrieval. Parsing feeds Index for chunking, embedding, and retrieval in the LlamaIndex ecosystem. Parsing output and spatial detail depend on the selected tier and configuration. |
| Security & compliance | ZDR is available on every plan. Zero data retention can be enabled on request. Extend supports SOC 2 Type II, HIPAA with BAAs, GDPR, and EU processing. AI and GPU subprocessors operate under contractual ZDR and no-training terms. | No training by default, with configurable caching. Parse and Extract files are cached for 48 hours unless caching is disabled. Indexed data has separate retention. SOC 2 Type II and Enterprise HIPAA/BAA options are documented. |
| Deployment & residency | Cloud, BYOC/VPC, and Hybrid. Extend documents three deployment models: managed Cloud in US or EU regions (EU hosting in Frankfurt), BYOC deployed into your own cloud account and VPC under your IAM and encryption policies with Extend managing deployment automation, and Hybrid, which keeps documents in your cloud while Extend runs inference. Extend does not currently offer a fully air-gapped deployment. | Managed SaaS and customer-hosted options. LlamaParse documents managed and single-tenant SaaS, BYOC, self-hosting, and regional endpoints. Confirm processing and storage locations for the chosen deployment. |
| Enterprise readiness | Document operations and enterprise controls in one platform. Enterprise includes SSO/SAML, RBAC, custom MSA/DPA/SLA, custom limits, and dedicated support, alongside processor versioning, evals, and review. | Enterprise identity and contracting options. SSO, RBAC, enterprise MSA/DPA, and HIPAA BAA options are documented. Teams still need to define application-specific quality gates and review operations. |
| Pricing | Free self-serve PAYG with no monthly minimum. Extend pricing includes 10,000 free credits, then $0.0125/credit. Optional Scale costs $500/month with 50,000 credits and $0.01 per additional credit. Operation and mode determine usage; extraction includes automatic parsing. | Credits vary by product and tier. The documented conversion is $1.25 per 1,000 credits. Parsing uses 1, 3, 10, or 45 credits/page before optional additions; extraction and indexing have separate rates. Compare total operation cost, not nominal credit prices. |
| Developer & agent experience | Typed SDKs and tools for developers and coding agents. Python, TypeScript, Java, and Go SDKs, REST, CLI, MCP, agent skills, machine-readable docs, and an open-source UI kit support building and operating document workflows. | SDKs and agent tools integrated with LlamaIndex. The platform quickstart covers Python, TypeScript, Go, Java, and CLI usage. MCP and agent skills support document processing from coding agents. |
Pricing: compare the workflow, not one parse call
Both vendors use credits, and the credit cost varies by product and mode. Compare the exact sequence of parse, extract, split, classify, indexing, evaluation, and review operations your application will run.
| Pricing dimension | Extend | LlamaParse |
|---|---|---|
| Free tier | 10,000 credits with full product access and no listed expiration | $0 per month with 10,000 monthly credits and community support |
| Entry paid tier | Pay As You Go at $0.0125 per additional credit and no monthly platform fee; zero data retention (ZDR) enabled on request | Starter at $50 per month with 40,000 monthly credits and metered overage subject to a configured spending limit |
| Growth tier | Scale at $500 per month with 50,000 credits, $0.01 additional credits, volume discounts, higher rate limits, Slack support, and custom retention agreements | Pro at $500 per month with 400,000 monthly credits and priority support |
| Enterprise | Custom pricing with BYOC/VPC or Hybrid deployment, agreements and SLA, SSO/SAML, advanced RBAC, multiple workspaces, custom models and limits, dedicated support, and BAA included | Custom credit allocation, rate limits, and dedicated support; enterprise identity, deployment, and BAA terms are agreed separately |
| Product scope | Parse, Extract, Classify, Split, Edit, Studio, evals, Composer, Review Agent, agentic OCR, and workflows | Parse, Extract, Classify, Split, and Index; product and tier determine credit consumption |
Current terms can change. Verify Extend pricing, LlamaParse pricing, and the exact credit schedule before modeling production cost.
Extend vs LlamaParse: which is right for you?
| Best fit use cases for Extend | Best fit use cases for LlamaParse |
|---|---|
| Measured accuracy on complex documents is the deciding factor. Use the open-source benchmarks as a starting point, then test the same documents and acceptance criteria in your intended production configuration. | Your application already uses LlamaIndex. Native Index integration can reduce the work needed to turn parsing output into retrieval for an existing LlamaIndex application. |
| Your output is a business object that drives action. Extract into a defined schema with citations and confidence for workflows where missing records or incorrect values affect downstream decisions. | Retrieval is the primary destination. Choose a direct path into chunking, embedding, and hosted indexing when your main deliverable is searchable document content. |
| You want one platform from development to production. Combine parse, extract, split, classify, edit, workflows, evals, and review without building each document-specific operation separately. | You already own the surrounding quality workflow. Parse and Extract can fit an application with established evaluation, validation, exception routing, and reviewer tooling. |
| You need to manage accuracy, latency, and cost. Select processing modes by workload and measure complete workflow cost at the accuracy threshold your application requires. | |
| Your team needs to evaluate changes and resolve exceptions. Versioned processors, evaluation sets, Review Agent, and a human review queue support controlled releases and correction of production output. | |
| You need a choice of deployment and data controls. Use managed Cloud in the US or EU, BYOC, or Hybrid, with ZDR available on request and enterprise identity and contracting options. |
What to test before choosing
Use the same 50 to 100 documents, schemas, and acceptance rules for both products.
- Include the longest documents, worst scans, deepest tables, charts, handwriting, and multilingual pages in the production distribution.
- Score parsing and extraction separately. A parser can produce readable markdown while dropping business records.
- Count expected rows before scoring field values. Report omissions, duplicates, and failed documents independently.
- Test both default and task-appropriate modes. Record every non-default setting.
- Measure whether each citation points to the exact source region, not only whether a value appears somewhere on the page.
- Change the schema and parser configuration, then measure whether evaluation and versioning prevent regressions.
- Run an actual review team through each platform interface and measure correction time and auditability.
- Price the complete workflow at expected volume, including retries, extraction, indexing, evaluation, and review operations.
Frequently asked questions
Is Extend more accurate than LlamaParse?
For production document workflows, the strongest like-for-like public evidence favors Extend: Extend Parse 2.0 leads LlamaParse Agentic on RealDoc-Bench field-level QA, and Extend MAX leads both LlamaParse modes by a wide margin on LongArray-Extract. LlamaIndex's ParseBench reports higher scores for LlamaParse Agentic, but it compares that multi-step agentic mode with Extend's Parse 1.0 markdown configuration rather than a task-configured Extend workflow. ParseBench therefore establishes an advantage over the Extend configuration tested by the paper, not over the complete or properly configured Extend product.
What is the best LlamaParse alternative for business documents?
Extend is the strongest alternative when business documents feed systems of record and the requirement extends beyond parsing into schema-defined extraction, packet splitting, classification, form editing, evaluation, citations, confidence, and platform-enabled review. LlamaParse remains a strong choice when the document path ends in LlamaIndex retrieval or hosted indexing.
Does LlamaParse support structured extraction?
Yes. LlamaParse Extract supports schema-based extraction with Pydantic or Zod and documents citation and confidence features. The difference is not whether extraction exists; it is how each platform handles the rest of production quality operations and downstream architecture.
Can I migrate from LlamaParse to Extend?
Yes. Map parse and extract outputs, recreate schemas, preserve citation semantics, and run both providers against the same evaluation set before switching production traffic.
Which platform is more enterprise-ready?
Both publish enterprise deployment and security options. Extend documents three deployment models: managed Cloud in US or EU regions, BYOC inside your own VPC under your IAM and encryption policies, and Hybrid. Its Enterprise tier adds custom agreements and SLA, SSO/SAML, advanced RBAC, multiple workspaces, custom models and rate limits, dedicated support, and deployed engineering. LlamaIndex publishes SSO, RBAC, managed SaaS, BYOC and self-hosted deployment, and Enterprise BAA options. Confirm the exact architecture and contract for the tier being purchased.
How do Extend and LlamaParse prices compare?
Both are credit-based. Extend starts with 10,000 free credits and self-serve pay as you go without a monthly platform fee, contract, or sales call; Scale at $500 per month is an optional volume tier, not the entry plan. LlamaParse has 10,000 free credits, a $50 Starter plan, and a $500 Pro plan. Credit consumption differs by operation and mode, so compare a complete production workflow rather than the nominal credit price.
