txtfetch vs LlamaParse

LlamaParse is credit-metered parsing, tuned for complex pdfs. Here's the honest comparison — pricing math, capabilities, and where each tool actually wins.

at a glance

LlamaParse

Billing
credits (per page, tiered by fidelity)
Rate used below
$0.00125/page
Free tier
~10,000 credits/month free (secondary source — treat as directional).

txtfetch

Billing
per document, regardless of page count
Rate used below
flat monthly quota — see plans
Free tier
500 documents/month, free, ongoing (Hobby plan)

capability table

CapabilityLlamaParsetxtfetch
Billing unitcredits (per page)per document
Format coveragePDF-first, common Office formats1,000+ formats (Apache Tika)
OCR for scans / images++
Table extraction++*
Complex layout fidelity+~*
Structured field extraction+not yet*
Self-hosted option
Single HTTP endpoint~+

Vendor-published benchmarks are marked directional throughout — see sources below. * txtfetch notes: Tables come back as structured rows/cells, not flattened text: ?format=markdown renders GFM pipe tables, ?format=json returns table elements with a cells array. Output is clean linear/structured text, not a visual layout reconstruction — by design, but worth knowing. Structured markdown and element-JSON document output ship today (?format=markdown / ?format=json). Schema-defined field extraction — pulling typed fields per your own schema — is on the roadmap, not shipped. We won't claim it early.

the cost calculator

Per page vs per document, worked out.

A 300-page PDF is 300 units of billing to LlamaParse. It's one document to txtfetch. Adjust the numbers to your own workload.

LlamaParse

Fast tier — 1 credit/page ($1.25 per 1,000 credits) · $0.00125/page

txtfetch

LlamaParse's figure is their cheapest OCR/base tier — forms, tables, and higher-fidelity models cost more on top. txtfetch bills a flat monthly document quota: the page count inside a document doesn't change your bill.

where llamaparse wins

  • Best-in-class fidelity on genuinely hard PDFs: multi-column layouts, embedded tables, math notation, and forms.
  • Higher tiers (Premium/Accurate) trade credits for materially better structure recovery on messy scans — a real dial we don't offer.
  • Native structured/JSON output modes for downstream LLM consumption, which we don't have yet.

where txtfetch wins

  • Breadth: 1,000+ formats through Apache Tika, not a curated list of a dozen file types.
  • One HTTP endpoint — pass a URL or upload a file, get text back. No SDK, no async job polling required.
  • Priced per document, so a 300-page report doesn't cost 300x a one-pager.
  • A durable free tier (500 documents/month, ongoing) rather than a time-boxed trial.

What we don't claim yet: schema-defined structured field extraction or an uptime SLA. Those ship later — see the capability table above.

sources

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