LlamaParse vs Reducto vs NuMind: Picking a Document-Parsing Vendor in 2026

Seven recent roundups of document parsers for AI pipelines, published between January and September 2026, name LlamaParse, Reducto, Unstructured and Docling as the default shortlist, and not one of them mentions NuMind.

That gap is not an oversight so much as a category error. LlamaParse and Reducto convert a document into markdown or structure-preserving JSON for retrieval. NuMind's NuExtract Platform pulls a fixed set of fields out of the same document instead, priced per token rather than per page. A team searching for "the best document parsing vendor" is often actually choosing between two different jobs: general-purpose conversion versus schema-bound extraction.

Picking the wrong one means re-parsing the whole archive later, at full price. This guide treats all three as real candidates, prices them on the same page, and names a winner for three specific situations rather than one universal pick.

The verdict, upfront

Pick Reducto if your documents are messy: scanned forms, handwritten fields, multi-column tables, and you need SOC 2 Type II or HIPAA sign-off before the vendor touches a single page. Pick LlamaParse if you are already building on the LlamaIndex framework and want the cheapest possible markdown conversion for a prototype, not a production pipeline with compliance requirements. Pick NuMind if the actual job is pulling ten named fields out of an invoice or a claim form into JSON, not producing a clean document for a retrieval index.

None of the three is a drop-in replacement for either of the others. That is the finding this guide's competitors skip.

What "document parsing" actually means here

Reducto's Parse tier and LlamaParse both take a PDF, scan or spreadsheet and return markdown or JSON with the layout preserved: headings, tables, reading order, page numbers. That output is built to be chunked and embedded for retrieval-augmented generation, so a coding agent or support bot can cite the right paragraph.

NuExtract does not produce a general-purpose document. It produces a JSON object matching a schema the user defines first, for example invoice_number, line_items, total_due. According to NuMind's own published benchmark, NuMind's open-weight NuExtract models score roughly nine F-score points above GPT-4.1 on extraction tasks the company tested. That is a real, useful capability. It is also not a substitute for turning a 40-page contract into markdown for a chat assistant to search.

Price, and the unit each vendor bills in

LlamaParse's v2 tiers run on credits at $1.25 per 1,000, across four parsing modes: Fast (1 credit a page), Cost-effective (3 credits), Agentic (10 credits) and Agentic Plus (45 credits), according to LlamaIndex's own pricing docs. That works out to roughly $0.00125 a page at the cheapest setting and $0.05625 a page at the most thorough one, a 45x spread inside one product. The free tier includes 10,000 credits a month, enough for about 10,000 pages at Fast or 3,300 pages at Cost-effective.

Reducto's Enterprise plan sits at the other end of that spread on price alone: Parse costs $10 per 1,000 pages ($0.01 a page) on the published rate card, with a Standard tier that bundles 15,000 free credits before billing starts, and Growth and Enterprise tiers priced on volume, according to Reducto's own pricing page.

NuExtract bills per token instead of per page, at $5 per million tokens through NuMind's API. That is not directly comparable to a per-page rate: a dense two-column financial statement costs more tokens per page than a mostly-blank form, so the same document can land on either side of the LlamaParse-Reducto price gap once it goes through NuExtract's tokenizer.

Accuracy on the documents that break simple parsers

Reducto's own comparison material claims its agentic OCR-correction layer adds up to 20 percentage points of extraction accuracy on messy real-world documents, the kind with skewed scans, merged table cells or handwritten annotations, next to a plain OCR pass. That is a vendor's own number, worth treating as a claim rather than an independent finding, but it lines up with the reason every third-party roundup checked for this piece put Reducto ahead of LlamaParse specifically on complex, non-digital-native documents.

For documents that are already clean, born-digital PDFs, the accuracy gap between the three narrows enough that price and workflow fit matter more than raw extraction quality. Free, open-source layout engines such as Unstructured and Docling handle that easier case well, and several of the roundups checked for this piece use one of them as the baseline every paid vendor is measured against.

Compliance, and where the data actually goes

Reducto is SOC 2 Type II audited and HIPAA-compliant with signed BAAs available, and it offers zero data retention by default on its Growth and Enterprise tiers: submitted data auto-deletes within 24 hours at the outside. It also runs in a customer's own VPC, on-prem, or fully air-gapped with no outbound network calls, which is the deployment shape a hospital or a bank's document pipeline usually has to clear before procurement will sign off.

NuExtract takes a different route to the same destination. Its models are published as open weights on Hugging Face, so a team that cannot send documents to any third-party API at all can run the extraction model entirely inside its own infrastructure, with no vendor in the data path once it is deployed. That is a stronger privacy position than "we promise not to retain your data", at the cost of running and maintaining the model yourself.

LlamaParse, as of this run, is cloud-only: there is no published on-prem or air-gapped option, so a regulated team that needs one is choosing between Reducto and NuExtract regardless of which produces the cleaner markdown.

Who should pick what

Reducto: regulated industries with ugly source documents

A healthcare team processing scanned prior-authorization forms, or a bank digitizing decades of paper contracts, is buying two things at once: an OCR layer that handles bad scans, and a compliance posture (HIPAA, SOC 2, air-gapped deployment) that a procurement team will actually approve. Reducto is built for that combination specifically.

LlamaParse: teams already on LlamaIndex, prototyping

A small team building a RAG demo on the LlamaIndex framework gets same-stack tooling, a free tier generous enough to index a few thousand pages before paying anything, and parsing modes cheap enough to iterate on without a procurement conversation. It is the right first choice for a prototype that has not yet earned a compliance review.

NuMind: structured fields, not a search index

An operations team that needs "pull the invoice number, the vendor name and the total from ten thousand PDFs a month into a spreadsheet" is not shopping for a document parser at all, even though the vendor pages get grouped together. NuExtract's schema-first design and open-weight self-hosting option fit that job better than teaching a general parser's markdown output to answer the same question.

The turn

The obvious objection to all of this: a four-person startup building its first RAG prototype does not need any of these three. Unstructured and Docling are free, open-source, and good enough for clean, born-digital PDFs, which is most of what an early prototype ingests.

That is true, and it is exactly why this guide is written for the team that has already outgrown the free layout engine, whether because its documents got messier, its volume got bigger, or a customer's security questionnaire started asking about SOC 2. Below that line, none of this comparison matters yet.

What switching actually costs

Every one of these vendors locks in more than an API contract. A pipeline built around LlamaParse's markdown output, or NuExtract's field schema, has usually already been chunked, embedded and indexed downstream. Re-parsing a 50,000-page archive at Reducto's published $10-per-1,000-page rate costs $500 in API calls alone, before counting the engineering time to re-chunk and re-embed everything that already went through a vector database once.

That is the real reason to get this choice right the first time rather than treating it as a cheap experiment to swap out later. If none of these three cleanly fits a team's actual mix of document mess, compliance requirements and budget, running the specifics through HokAI's Smart Match is faster than testing all three APIs by hand.

The three products are not really rivals. They are three different answers to "what do you do with a PDF", and the moment a team has to ask that question a second time, for a different kind of document, is when it finds out whether it picked the right one the first time.

Frequently asked questions

Is NuMind a document parser like LlamaParse and Reducto?

Not directly. LlamaParse and Reducto convert a whole document into markdown or JSON for a retrieval index. NuMind's NuExtract Platform pulls a defined set of fields out of a document into a fixed JSON schema, which is a different job even though the tools get compared as if they compete.

How much does LlamaParse cost per page in 2026?

LlamaParse bills in credits at $1.25 per 1,000. Its four parsing modes cost 1, 3, 10 or 45 credits a page, which works out to roughly $0.00125 to $0.05625 a page. The free tier includes 10,000 credits a month.

Is Reducto HIPAA compliant?

Yes. Reducto is SOC 2 Type II audited and offers HIPAA compliance with signed BAAs, plus zero data retention by default on its Growth and Enterprise tiers. It also supports VPC, on-prem and fully air-gapped deployment for regulated teams.

Can NuExtract run privately or on-prem?

Yes, and further than most vendors go. NuMind publishes its NuExtract models as open weights on Hugging Face, so a team can self-host the extraction model entirely inside its own infrastructure with no vendor in the data path at all.

Which of the three is free to prototype with?

LlamaParse has the most generous entry point: 10,000 free credits a month, enough for thousands of pages before any billing starts. Reducto's Standard tier includes 15,000 free credits. Neither free tier is meant to carry a production workload indefinitely.

Covered in this guide

• NuExtract Platform: NuMind's NuExtract API pulls structured JSON from PDFs and scans, claiming a 9-point F-score edge over GPT-4.1 on its own extraction benchmark.
• Reducto: Reducto turns PDFs, scans, and spreadsheets across 30+ file types into structured JSON for RAG pipelines and AI agents, with agentic OCR correction.

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