> Source: https://txtfetch.com/compare/libraries/mineru > Plain-text twin — every page on txtfetch.com has one. https://txtfetch.com/text --- # txtfetch vs MinerU MinerU is an open-source library you run yourself. txtfetch is one HTTP call. Here's an honest look at the licence, the operational cost, and where each one wins. ## What MinerU is MinerU is built by OpenDataLab. A VLM-and-OCR document parser with the broadest native OCR language coverage of the five. MinerU moved off AGPL-3.0 in its 3.1.0 release to a custom licence built on top of Apache-2.0. Commercial use is free below two thresholds: 100 million monthly active users, or $20 million in monthly revenue. Both thresholds count your affiliates too. Cross either one and you need a separate commercial licence. The licence also requires you to name MinerU in any product or service you build on it. MinerU changed licences this recently, so double-check which version, and which licence, you are actually pinning. Licence checked 2026-09. See [the project's own LICENSE file](https://github.com/opendatalab/MinerU/blob/master/LICENSE.md). Checked against the project's own LICENSE file, not a summary of it. A licence can change between releases, so check the LICENSE of the exact version you pin, not this page. This is a factual summary, not legal advice. at a glance MinerU **Code licence**: MinerU Open Source License, a custom licence based on Apache-2.0 **Model-weights licence**: Covered by the same MinerU Open Source License as the code **Install**: pip install mineru (or an extras variant). Model weights download from Hugging Face or ModelScope on first run. **Model weights**: A VLM model (around 1.2B parameters in its current release) plus an OCR model stack, both downloaded on first use. **GPU**: Depends on the backend. The CPU-capable pipeline backend runs without one; the higher-accuracy VLM and hybrid-engine backends need a GPU (or Apple mlx) for realistic throughput. Several Chinese domestic AI accelerators are also supported directly. **Formats**: Native PDF, DOCX, PPTX, and XLSX parsing, plus images, per the project's README. **Output**: Markdown and JSON, with formulas converted to LaTeX and tables to HTML. **OCR**: A dual VLM-plus-OCR engine with 109-language OCR recognition. That's the broadest bundled OCR language list of the five. txtfetch **Code licence**: N/A — hosted API, no code to license **Model-weights licence**: N/A — no weights on your infrastructure **Install**: None. One HTTP call. **Model weights**: None on your side. Tika and Tesseract run on ours. **GPU**: None needed. quality=premium routes to a VLM on our infrastructure. **Formats**: Every format on the coverage list, one endpoint. **Output**: Text, Markdown, or element JSON. **OCR**: Standard tier: eng, osd. quality=premium for a hard scan. See /languages. capability table | Capability | MinerU | txtfetch | | --- | --- | --- | | Hosting | self-hosted only | hosted API* | | Ships neural model weights | yes | no | | GPU required | partial | no* | | Table extraction | yes | yes | | OCR engine bundled | yes | yes* | | Structured or JSON output | yes | yes* | | Built-in chunking for RAG | no | no* | | Single HTTP endpoint | partial | yes | \* txtfetch notes: One HTTP call. No install, no model download, no server to run and patch. The standard tier runs on Tika and Tesseract, CPU only. quality=premium routes a document to a vision-language model on our infrastructure, not yours. The standard OCR tier ships English trained data plus script detection only (TESSDATA\_LANGS=eng osd). See /languages for the per-language detail and quality=premium for a hard scan. ?format=markdown and ?format=json ship today. Schema-defined field extraction, pulling named fields to your own schema, is on the roadmap, not shipped yet. txtfetch returns text, Markdown, or element JSON. Chunking stays a caller-side step, the same reasoning behind every guide on /fixes. No accuracy or speed figure is measured against MinerU on this page. See [/benchmarks](https://txtfetch.com/benchmarks) for txtfetch's own measured numbers and their caveats. where mineru wins - 109-language OCR recognition, bundled by default. That's the strongest coverage of the five for non-Latin and CJK scripts. - Cross-page table merging and reading-order reconstruction aimed specifically at complex, multi-page layouts. - Native parsing of PDF, DOCX, PPTX, and XLSX without first converting through PDF, unlike tools that only read Office formats via a conversion step. - Multiple backend choices (a CPU-only pipeline, plus GPU-backed VLM and hybrid engines) so you can trade cost against accuracy per workload. the work you still own MinerU is free to run. Running it in production is a separate job. This is the checklist that job includes. - Downloading and caching MinerU's VLM and OCR model weights, and provisioning a GPU if you need the higher-accuracy backends at real volume. - Naming MinerU in your product or service, a condition the licence attaches to any online service built on it. - Tracking your own combined monthly active users and revenue against the licence's 100 million MAU / $20 million revenue thresholds. - Patching MinerU and its model stack, and re-reading the licence on every upgrade, since it changed once already in 2026. where txtfetch wins - One HTTP call. No install, no model download, no GPU to provision, and no server to patch. - The standard OCR tier ships English trained data plus script detection only (`TESSDATA_LANGS=eng osd`). See [/languages](https://txtfetch.com/languages) for the per-language detail, and request `quality=premium` for a hard non-English scan. - A durable free tier (500 documents/month, ongoing), so trying it costs nothing and no card. txtfetch strips HTML markup, not boilerplate, the same as /fixes describes it. Nav, footer, and cookie-banner text still comes back as ordinary text. Deciding what's chrome versus article stays a caller-side step. We also don't ship schema-defined field extraction yet. See the capability table above for the full list. the same job, one call This is the whole integration: no install, no model download, no GPU. ``` curl -s -X POST "https://api.txtfetch.com/v1/extract?format=markdown" \ -H "Authorization: Bearer $TXTFETCH_KEY" \ -F file=@document.pdf ``` frequently asked questions **Is MinerU still AGPL-licensed?**: No, not since its 3.1.0 release. MinerU moved to a custom MinerU Open Source License built on Apache-2.0. It's free below 100 million monthly active users, or $20 million in monthly revenue, counting your affiliates. It also requires naming MinerU in any service you build on it. **Does MinerU need a GPU?**: Only for its higher-accuracy backends. The pipeline backend runs on CPU. The VLM and hybrid-engine backends need a GPU, or Apple's mlx, for realistic throughput. **What makes MinerU's OCR different from the others here?**: It bundles OCR recognition across 109 languages by default. That's the broadest language list of the five projects on this page, and it matters most for non-Latin and CJK-script documents. sources - [MinerU: LICENSE.md (custom, Apache-2.0-based)](https://github.com/opendatalab/MinerU/blob/master/LICENSE.md) Accessed 2026-09 - [MinerU: README (changelog, formats, backends)](https://github.com/opendatalab/MinerU) Accessed 2026-09 - [mineru on PyPI](https://pypi.org/project/mineru/) Accessed 2026-09 Checked against the project's own LICENSE file, not a summary of it. A licence can change between releases, so check the LICENSE of the exact version you pin, not this page. This is a factual summary, not legal advice. other open-source parsers - [txtfetch vs Docling →](https://txtfetch.com/compare/libraries/docling) - [txtfetch vs MarkItDown →](https://txtfetch.com/compare/libraries/markitdown) - [txtfetch vs PyMuPDF4LLM →](https://txtfetch.com/compare/libraries/pymupdf4llm) - [txtfetch vs Marker →](https://txtfetch.com/compare/libraries/marker) - [All open-source parsers →](https://txtfetch.com/compare/libraries) ## Keep the library. Add the hard formats. Some teams run both. Send only the files MinerU cannot read. [Read the quickstart →](https://txtfetch.com/docs) [Compare self-hosted Tika →](https://txtfetch.com/compare/self-hosted-tika)