---
title: "Deploy MinerU v3.4.4 | PDF-to-Markdown API for RAG, CPU-Ready and Preloaded"
description: "[v3.4.4] PDF/Office to Markdown for RAG. CPU default, models preloaded."
category: "AI/ML"
url: https://railway.com/deploy/mineru-v344-or-pdf-to-markdown-api-for-r
---

# Deploy MinerU v3.4.4 | PDF-to-Markdown API for RAG, CPU-Ready and Preloaded

[v3.4.4] PDF/Office to Markdown for RAG. CPU default, models preloaded.

**[Deploy MinerU v3.4.4 | PDF-to-Markdown API for RAG, CPU-Ready and Preloaded on Railway](https://railway.com/template/mineru-v344-or-pdf-to-markdown-api-for-r)**

- **Creator:** SuperSlowSloth
- **Category:** AI/ML

## Template content

### mineru

- **Image:** ghcr.io/bon5co/mineru-railway:latest
- **Health check:** /health
- **Public domain:** Yes

## Documentation

# Deploy and Host MinerU on Railway

MinerU is OpenDataLab's document parsing engine: PDFs, images and Office files in,
LLM-ready Markdown and JSON out, with layout detection, OCR in 80+ languages,
table-structure recognition and formula recognition. This template runs its
`mineru-api` HTTP server on CPU — no GPU, no per-page cloud OCR fees, and no
third-party service holding your documents.

It deploys as **one service on a volume**, from a prebuilt image, with the parsing
models already inside it.

## About Hosting MinerU

MinerU is normally packaged for a GPU box on a trusted network, and two of its
defaults do not survive the move to a one-click public deploy. This template
changes both, in the image, so the deployer never has to know about them.

**The default request parses.** MinerU 3.4's default backend is `hybrid-engine`,
which expects a local VLM and a GPU. On a CPU container a request that simply
omits `backend=` does not fail cleanly — it downloads roughly 2 GB of additional
VLM weights and then runs vision-language inference on the CPU, taking tens of
minutes for a paper-length PDF. Railway's edge gives up at about five minutes, so
the caller sees `Application failed to respond` while the container keeps working,
and keeps billing. Here `pipeline` is the server's default, so a plain
`POST /file_parse` with a file and nothing else returns Markdown.

**Threads match the container.** MinerU's pipeline is torch end to end, and torch
sizes its thread pool from the cores it can see — which inside a container is the
host's core count, not your plan's quota. The entrypoint reads
`/sys/fs/cgroup/cpu.max` and sets `OMP_NUM_THREADS` from it before Python imports
torch, which is the only moment torch reads it.

**Models are already in the image.** The layout, OCR, table and formula models are
baked in at build time and `MINERU_MODEL_SOURCE=local` is pinned, so the container
needs no network to parse, the first request is as fast as the thousandth, and a
redeploy never re-downloads 1.5 GB.

**The API is not open to the internet.** `mineru-api` ships no authentication of
any kind. This template generates a `MINERU_API_KEY` and requires it on every
parsing route, leaving `/health` and `/docs` public.

## Why Deploy MinerU on Railway

Document parsing is bursty: heavy while a corpus is being ingested, idle in
between. Railway bills what the container actually uses, gives the service a
volume for its output and an HTTPS URL for your pipeline to call, and redeploys it
without you rebuilding a 3 GB image. Because the image is prebuilt and the models
are baked in, a deploy is a pull and a start — not a ten-minute torch build on your
build minutes.

## Common Use Cases

- Ingesting PDFs into a RAG pipeline or vector store as clean Markdown, with
  headings, tables and formulas preserved rather than flattened.
- Giving an agent or workflow (n8n, LangChain, LlamaIndex) a private
  `POST /file_parse` endpoint instead of a metered cloud OCR API.
- Converting scanned or mixed-language archives — 80+ OCR languages, including
  Chinese, Japanese, Korean, Arabic, Cyrillic, Devanagari and Thai.

## Dependencies for MinerU Hosting

- A Railway service running the prebuilt image `ghcr.io/bon5co/mineru-railway`.
- A Railway volume mounted at `/data` for async task output.
- `MINERU_API_KEY`, generated per deploy, sent as `Authorization: Bearer …` or
  `X-API-Key: …`.

### Deployment Dependencies

- [MinerU](https://github.com/opendatalab/MinerU) — the upstream engine (Apache-2.0 / AGPL components per upstream's notice)
- [MinerU documentation](https://opendatalab.github.io/MinerU/)
- [bon5co/mineru-railway](https://github.com/bon5co/mineru-railway) — the wrapper image built for this template

### Implementation Details

Parse a document — no `backend` parameter needed:

```bash
curl -X POST https:///file_parse \
  -H "Authorization: Bearer $MINERU_API_KEY" \
  -F "files=@paper.pdf" \
  -F "lang_list=en" \
  -F "return_md=true"
```

Large documents are better submitted asynchronously — `POST /tasks` returns a task
id, `GET /tasks/{id}` reports status and `GET /tasks/{id}/result` returns the
output once it is ready. Results live on the volume under `/data/output`.

Interactive documentation is at `https:///docs`, and
`https:///health` is the unauthenticated health endpoint Railway uses.


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