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Reducto vs LlamaParse

Reducto offers industry-leading accuracy, beating LlamaParse on parse and extract accuracy metrics at a fraction of the price.

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Benchmarks

More accurate at every price point

Each dot is one parsing configuration. Higher is more accurate, further left is cheaper. Every LlamaParse tier has a Reducto model that is both more accurate and cheaper.

r-1 mini is more accurate than LlamaParse Agentic (65.7% vs 60.0% of pages with no serious error) at $1 vs $12.50 per 1,000 pages.
12.5x cheaper
r-1 mini is more accurate than LlamaParse Agentic (65.7% vs 60.0% of pages with no serious error) at $1 vs $12.50 per 1,000 pages.
r-1 beats LlamaParse Agentic Plus, its top parse tier (76.3% vs 72.9%), at $10 vs $56.25 per 1,000 pages.
5.6x cheaper
r-1 beats LlamaParse Agentic Plus, its top parse tier (76.3% vs 72.9%), at $10 vs $56.25 per 1,000 pages.
Extraction precision on LongExtractionBench: Reducto Deep Extract vs LlamaExtract Agentic, on 225 documents averaging 358 pages.
99.6% vs 80.0%
Extraction precision on LongExtractionBench: Reducto Deep Extract vs LlamaExtract Agentic, on 225 documents averaging 358 pages.

Parsing: price vs accuracy

Share of 2,000 public pages with no serious error, scored by the same AI judge

ReductoLlamaParse
50%55%60%65%70%75%80%$0$20$40$60Price per 1,000 pages (cheaper to the left)Pages with no serious errorr-1 mini65.7% · $1r-176.3% · $10LlamaParse Cost-effective53.4% · $3.75LlamaParse Agentic60.0% · $12.50LlamaParse Agentic Plus72.9% · $56.25

Extraction: LongExtractionBench

Precision on 225 long documents, independently published by micro1

Reducto Deep Extract99.6%

225/225 completed · 99.6% recall

LlamaExtract Agentic80.0%

203/225 completed · 77.5% recall

Parsing: 2,000 public-document pages across seven industries and six page types. A page counts only if it has no serious error; failed parses count as serious errors, and figure descriptions are excluded. Prices are list prices in USD per 1,000 pages; LlamaParse tiers are 3, 10, and 45 credits per page at $1.25 per 1,000 credits. Extraction: LongExtractionBench, commissioned by Reducto and independently diligenced and published by micro1. The two benchmarks measure different tasks on different datasets. Full methodology in the r-1 mini launch post.

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Migration credits

If you're using another document processor, we'll give you up to $5,000 in credits to migrate your workload to Reducto.

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At a glance

How Reducto and LlamaParse compare

Both are document AI platforms. The practical differences are product scope, ecosystem fit, published extraction evidence, deployment options, and the configuration your workload requires.

DimensionReductoLlamaParse
Platform scope
Parse, Extract, Classify, Split, Edit, Studio, and MCP.
Parse, Extract, Classify, Split, Sheets, Index, and MCP; Verify in preview.
Published extraction evidence
Yes: 99.6% precision and recall; 225/225 completed on LongExtractionBench.
Partial: 80.0% precision, 77.5% recall; 203/225 completed in the benchmark.
Complex tables and charts
Yes: Markdown/HTML tables, merged cells, nested headers, figure summaries; optional advanced chart extraction.
Yes: Layout-aware tables, granular boxes, and specialized chart parsing.
Citations and grounding
Yes: Optional per-field source text, page, bounding box, and confidence.
Yes: Optional granular parse boxes and per-field Extract citations.
Enterprise deployment
Yes: Managed cloud, hybrid VPC, full VPC/on-prem, and air-gapped paths.
Yes: Managed regional cloud and Enterprise self-hosted BYOC.
Compliance and data residency
Yes: SOC 2 Type II; HIPAA/BAA and 24-hour data expiry on Growth+; EU and AU endpoints.
Yes: SOC 2 Type 2, HIPAA, BAAs on Enterprise, North America and Europe regions.
Throughput behavior
Yes: Per-model, per-region page concurrency by tier (US r-1: 500 to 2,000+; EU is half); excess work queues instead of failing.
Partial: 5 to 100 concurrent parse jobs by plan; per-endpoint QPS caps return 429.
Agent tooling
Yes: SDKs, CLI, Studio, and MCP including document editing.
Yes: SDKs, CLI, LlamaCloud UI, LlamaIndex integration, and MCP.
Public pricing inputs
r-1 mini $1 and r-1 $10 per 1,000 pages; $150 in free credits.
$1.25/1,000 credits; parse tiers use 1–45 credits/page.

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The comparison in depth

Where the differences actually show up

Extraction accuracy, measured
LongExtractionBench, an independent benchmark conducted by micro1, evaluated seven extraction systems on 225 documents averaging 358 pages and roughly 88,700 ground-truth fields each. Reducto Deep Extract completed 225/225 documents with 99.6% precision, 99.6% recall, and 99.3% leaf accuracy. LlamaExtract Agentic completed 203/225 with 80.0% precision, 77.5% recall, and 88.9% leaf accuracy. Reducto commissioned the benchmark and created the methodology for drafting ground truth and running and grading systems; micro1 sourced the corpus, reconciled and verified human annotations, conducted independent technical diligence, and published the results. This is evidence for long-document structured extraction, not a universal parsing leaderboard. In production, Anterior measured 99.24% accuracy with Reducto on real patient cases, compared with 85% for human reviewers.
Complex layouts, tables, and charts
Both platforms document capabilities for difficult layouts. Parse r-1 reads text, tables, figures, and layout together in one pass, with source grounding. It supports Markdown/HTML table output, merged cells, nested headers, and figure summaries; advanced chart extraction is available as an additional step. In preview, r-1 is faster than Reducto's previous agentic pipeline, with 20% lower error. Legacy parsing and custom agentic processing remain available. LlamaParse documents layout-aware table extraction, granular word, line, and cell bounding boxes, and higher tiers for complex tables, charts, scans, and dense financial reports. Test both with the exact tier and options you expect to run in production.
Two platforms, different centers of gravity
LlamaParse's current platform includes Parse, Extract, Classify, Split, Sheets, and Index under one API and SDK surface. Verify, a document-authenticity review product, is published in preview. Reducto includes Parse, Extract, Classify, Split, and Edit, plus Studio. Edit is a meaningful distinction when a workflow must modify documents after understanding them; LlamaParse's hosted Index and Sheets products matter when retrieval infrastructure or spreadsheet-region processing belongs in the same buying decision.
Citations and reviewability
Both vendors document sub-page grounding. Reducto citations can return source content, page, bounding box, and confidence for extracted values when enabled. LlamaParse can return granular word, line, and table-cell boxes, while LlamaExtract citations can include page, matching source text, bounding boxes, and page dimensions. Evaluate citation coverage, precision, and reviewer workflow rather than availability alone.
Enterprise deployment and compliance
Reducto documents SOC 2 Type II; HIPAA processing and BAAs on Growth and Enterprise; EU/AU data-residency endpoints; and managed, hybrid-VPC, full-VPC/on-prem, and air-gapped paths. On Growth and Enterprise, API data expires within 24 hours, except Studio jobs and explicitly persisted results. LlamaCloud documents SOC 2 Type II, HIPAA, Enterprise BAAs, North America and Europe regions, and Enterprise self-hosted BYOC on Kubernetes in AWS, Azure, or GCP. Confirm exact plan, region, retention, support, and contractual terms with either vendor.
Agent and API workflows
Both platforms offer SDKs, CLI access, visual tools, and multi-product MCP servers. Reducto MCP exposes Parse, Extract, Classify, Split, and Edit. LlamaParse MCP exposes Parse, Extract, Classify, Split, and Index. LlamaParse has a natural advantage for teams standardized on LlamaIndex; Reducto has a documented advantage when document editing belongs in the same agent tool surface.
Throughput and limit behavior
The two platforms shape load differently. Reducto caps concurrent pages per model, tier, and region. In the US, Standard allows 500 r-1 pages and 50 r-1 mini pages, Growth up to 2,000 and 1,000, and Enterprise is custom. EU limits are half. Work above the cap queues rather than failing. Separate per-second rate limits still return 429 at the edge. LlamaCloud publishes per-endpoint request caps that return 429 when exceeded (20 requests per minute on the free tier), and its pricing page lists 5 to 100 concurrent parse jobs depending on plan. Size the plan against your peak, and decide whether retry handling or queueing is the behavior you want there.
Pricing the configuration you will run
Reducto includes $150 in free credits. Parse r-1 is $0.01/page, Extract is $0.02/page, and Deep Extract is $0.04/page, with parsing included in both extraction prices. You can budget by page count instead of estimating variable credit usage, with no separate parsing bill for extraction. LlamaParse charges $1.25 per 1,000 credits, with current parse tiers at 1, 3, 10, or 45 credits per page; Extract and other products add their own usage. These tiers are not quality-equivalent. Compare cost per accepted document, including retries, extraction, storage, indexing, and reviewer time. See processing rates.
Migration and coexistence

What to check before switching

  • Identify whether you are replacing parsing, extraction, or additional managed services.
  • Map document structure, table output, page references, and citations into the formats your application expects.
  • Account for differences in job submission, completion handling, and retries.
  • Run a held-out document set before changing production traffic.
  • Include adaptation and review effort in the cost comparison.

Reducto can provide document processing while LlamaIndex remains part of the application or retrieval stack. Replacing a parser does not automatically replace indexing and retrieval.

Considering additional vendors? See our LlamaParse alternatives guide.

Which fits your team

Who should pick which

Both can support production workflows. The better fit depends on the products, ecosystem, evidence, and deployment model your team values.

Choose Reducto if…

  • Your highest-risk step is complete, schema-valid extraction from long, table-heavy documents.
  • You want document editing alongside parsing, extraction, classification, and splitting.
  • Reviewers need field-level source text, page references, bounding boxes, and confidence metadata.
  • You require an Australian data-residency endpoint or a documented path to VPC, on-prem, or air-gapped deployment.
  • You want to reproduce Reducto's published LongExtractionBench result on your own corpus.

LlamaParse may be a fit if…

  • Your application already uses LlamaIndex or LlamaCloud and native integration reduces engineering work.
  • You want hosted indexing and retrieval or spreadsheet-region processing inside the same platform as parsing.
  • You want multiple parsing tiers so suitable documents can use lower-cost modes.
  • You need managed North America/EU regions or Enterprise Kubernetes deployment in your cloud.
FAQ

Common questions

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Further reading

Research before you choose

Document work starts here

Compare on your own documents

Sign up with $150 in free credits, freeze both configurations, and compare completion, accuracy, citations, reviewer time, latency, and cost.

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