mineru-4.0.0-released

opendatalab/MinerUmineru-4.0.0-releasedSep 16, 2026by myhloli

Upgrading?

AI Summary

MinerU 4.0 is a major overhaul introducing a tiered parsing quality system (flash, basic, standard, advanced), native multi-format document parsing via DocVortex, a local document library for agent workflows, and unified SDK/API tools.

Key Highlights

  • Four-tier parsing quality system replacing the old backend selection (pipeline/vlm/hybrid).
  • Native multi-format parsing (PDF, Office, EPUB, etc.) without conversion to PDF.
  • Local document library with stable locators (`doc:{id}/...`) for agent reading and verifiable citations.
  • Independent configuration for small models (ONNX/Torch) and VLM engines.
  • Unified V1 API and result models across SDK, CLI, and WebUI.

Breaking Changes

  • CLI entrypoints changed from 'mineru' to 'mineru parse' or 'mineru-kit parse'.
  • Configuration moved from 'mineru.json' to '$MINERU_HOME/config.yaml'.
  • Legacy result JSON handling changed; old artifacts should be re-parsed.
  • Python version requirements updated (>=3.10,<3.15).
  • Dependency extras renamed (e.g., mineru[core] -> base package).

New Features

  • DocVortex integration for native document parsing.
  • New 'mineru' command family (parse, read, find, search, show, list, watch, scan).
  • Background service support (`mineru server start`).
  • Telemetry control and privacy-first defaults.
  • Nine rendering targets (Markdown, HTML, LaTeX, DOCX, EPUB, PDF, etc.).

Full Release Notes

## What's Changed

- 2026/09/16 4.0.0 Released

  MinerU 4.0 is a major release that rebuilds the project around **tiered parsing quality**, **native multi-format document parsing**, **a local document library for agent reading**, and **unified SDK / API / service tools**. The main updates include:

  - Four parsing tiers
    - The 3.x `pipeline` / `vlm` / `hybrid` backend selection is replaced by four quality tiers: `flash`, `basic`, `standard`, and `advanced`.
    - `flash` parses native PDF text and digital documents without inference models, for discovery, preview, and indexing. `basic` runs small models for OCR, formulas, and tables, and can run on CPU. `standard` (the default reading quality) combines small models with the VLM for complex layouts. `advanced` spends more inference compute for maximum quality on difficult documents.
    - PDF and images support all four tiers; Office, OpenDocument, EPUB, OFD, HTML, and CSV/TSV are parsed locally at `flash` tier.

  - Native multi-format parsing
    - Supported inputs now cover PDF, images, DOC/DOCX, PPT/PPTX, XLS/XLSX, RTF, ODT/ODS/ODP, EPUB, OFD, HTML, and CSV/TSV. [DocVortex](https://github.com/myhloli/docvortex) provides native document parsing: no conversion to PDF, no model downloads.
    - Plain-text files (`.txt`, `.md`, ...) are read directly instead of parsed.

  - Local document library and agent reading
    - New `mineru` command family: `parse`, `read`, `find`, `search`, `show`, `list`, `watch`, `scan`, plus cache control (`invalidate`, `forget`, `cleanup`) and a background service (`mineru server start / status`).
    - `mineru parse` defaults to the first 10 PDF pages and returns a continuation command (`next_request`), so long documents are read progressively page by page instead of loaded at once.
    - Stable locators such as `doc:{id}/tier:{tier}/page:{page}/block:{block}` support follow-up reads, page/block image export, and verifiable citations. The README embeds an Agent Guide covering these workflows.
    - Privacy first: parsing is local by default, and documents are uploaded only when `--remote` is passed explicitly; anonymous telemetry can be inspected and disabled (`mineru telemetry status`).

  - Independent model configuration
    - Small models (ONNX or Torch) and the VLM engine (llama.cpp, vLLM, or LMDeploy) are now configured independently via `model.small_backend` and `model.vlm.engine`; `model.stack` / `--stack` are removed.
    - The base package works out of the box: ONNX CPU small models plus a llama.cpp VLM in Vulkan mode. `mineru[torch]` adds Torch small-model dependencies; `mineru[full]` also installs vLLM (Linux) or LMDeploy (Windows); Apple Silicon installs Torch by default and runs the VLM with llama.cpp.
    - New 4.0 model bundles `MinerU-4_models_onnx` / `MinerU-4_models_torch` (PP-DocLayoutV2, PP-OCRv6 Tiny Det + Small Rec, PP-FormulaNet plus-M, seal OCR, and shared table models), downloaded and verified with `mineru-kit models download / verify`.

  - Unified tools and V1 API
    - The Python SDK, stateless batch conversion (`mineru-kit parse`), the multi-service Router, and the Gradio WebUI (`mineru-webui`) share one structured result model.
    - The HTTP service is rebuilt around V1 (`/v1/health`, `/v1/tiers`, `/v1/uploads`, `/v1/parse/jobs`, `/v1/files`); legacy `/file_parse` and `/tasks` are not provided.

  - Structured results and nine rendering targets
    - One document model renders to Markdown, HTML, LaTeX, DOCX, EPUB, PDF, Structured Content, and Content List V1/V2; each entrypoint exposes its own subset of exports. See [Output Formats and Result Contract](https://opendatalab.github.io/MinerU/reference/output_files/).
    - Results carry a versioned shared schema, and PDF page ranges (`1-5,8,r3-r1`; `r1` is the last page, `all` selects the whole document) behave consistently across CLI, library, API, and SDK.

  - Breaking changes and migration
    - Entrypoints: `mineru -p input.pdf -o output` becomes `mineru parse input.pdf --pages all -o output.md` (library) or `mineru-kit parse input.pdf -o output.md` (one-off conversion); `mineru-gradio` becomes `mineru-webui`; `-m all` becomes `mineru-kit models download --tier standard`.
    - Extras and runtime: `mineru[core]` / `mineru[pipeline]` are replaced by the base package, `mineru[torch]`, and `mineru[full]`; Python `>=3.10,<3.15`.
    - Configuration now lives in `$MINERU_HOME/config.yaml`; the old `mineru.json` is no longer read.
    - Legacy result JSON is auto-converted only for cached Doclib history; old artifacts saved elsewhere should be re-parsed.
    - Existing AMD and vendor accelerator adaptations remain on `mineru<4`.
    - See the [3.x → 4.0 migration guide](https://opendatalab.github.io/MinerU/reference/migration_4/) for the full list.

  With 4.0, MinerU grows from a document conversion tool into a privacy-first document platform: tiered quality, native multi-format parsing, a searchable local library with stable citation locators for agents, and unified interfaces. Get started with the [Quick Start](https://opendatalab.github.io/MinerU/quick_start/), [Tiers and runtimes](https://opendatalab.github.io/MinerU/usage/tiers/), and [SDK and API](https://opendatalab.github.io/MinerU/usage/sdk_api/) pages; the full release history is in the [changelog](https://opendatalab.github.io/MinerU/reference/changelog/).

- 2026/09/16 4.0.0 发布

  MinerU 4.0 是一次大版本重构,围绕 **分档解析质量**、**原生多格式文档解析**、**面向 Agent 阅读的本地文档库** 与 **统一的 SDK / API / 服务工具** 重新打造。主要更新内容包括:

  - 四档解析质量(tier)
    - 3.x 的 `pipeline` / `vlm` / `hybrid` 后端选择升级为 `flash`、`basic`、`standard`、`advanced` 四档质量档位。
    - `flash` 原生解析 PDF 文本层与电子文档,无需推理模型,适合发现、预览与索引;`basic` 使用小模型完成 OCR、公式与表格识别,可在 CPU 环境运行;`standard`(默认阅读质量)结合小模型与 VLM 处理复杂版面;`advanced` 在标准能力上投入更多推理算力,应对高难度文档。
    - PDF 与图片支持全部四档;Office、OpenDocument、EPUB、OFD、HTML、CSV/TSV 在本地以 `flash` 档解析。

  - 原生多格式解析
    - 支持的输入覆盖 PDF、图片、DOC/DOCX、PPT/PPTX、XLS/XLSX、RTF、ODT/ODS/ODP、EPUB、OFD、HTML 与 CSV/TSV;[DocVortex](https://github.com/myhloli/docvortex) 提供原生文档解析,无需转 PDF、无需下载模型。
    - 纯文本文件(`.txt`、`.md` 等)直接读取,不做解析。

  - 本地文档库与 Agent 阅读
    - 新增 `mineru` 命令族:`parse`、`read`、`find`、`search`、`show`、`list`、`watch`、`scan`,以及缓存管理(`invalidate`、`forget`、`cleanup`)与后台服务(`mineru server start / status`)。
    - `mineru parse` 默认读取 PDF 前 10 页并返回续读命令(`next_request`),长文档按页渐进阅读,无需一次性载入。
    - `doc:{id}/tier:{tier}/page:{page}/block:{block}` 等稳定定位符支持后续读取、页/块图片导出与可验证引用;README 内置 Agent Guide 描述这些工作流。
    - 隐私优先:默认全程本地解析,只有显式使用 `--remote` 才会上传文档;匿名遥测可随时查看与关闭(`mineru telemetry status`)。

  - 模型配置独立化
    - 小模型(ONNX / Torch)与 VLM 引擎(llama.cpp / vLLM / LMDeploy)通过 `model.small_backend` 与 `model.vlm.engine` 独立配置;移除 `model.stack` 与 `--stack`。
    - 基础包开箱即用:小模型走 ONNX CPU,VLM 使用 llama.cpp Vulkan 模式;`mineru[torch]` 增加 Torch 小模型依赖,`mineru[full]` 额外安装 vLLM(Linux)或 LMDeploy(Windows);Apple Silicon 默认安装 Torch 并以 llama.cpp 运行 VLM。
    - 新的 4.0 模型包 `MinerU-4_models_onnx` / `MinerU-4_models_torch`(PP-DocLayoutV2、PP-OCRv6 Tiny Det + Small Rec、PP-FormulaNet plus-M、印章识别与共享表格模型),使用 `mineru-kit models download / verify` 下载与校验。

  - 统一工具链与 V1 API
    - Python SDK、无状态批量转换(`mineru-kit parse`)、多服务 Router 与 Gradio WebUI(`mineru-webui`)共享同一套结构化结果。
    - HTTP 服务重构为 V1(`/v1/health`、`/v1/tiers`、`/v1/uploads`、`/v1/parse/jobs`、`/v1/files`);不再提供旧的 `/file_parse` 与 `/tasks`。

  - 结构化结果与九种渲染目标
    - 一套文档模型渲染为 Markdown、HTML、LaTeX、DOCX、EPUB、PDF、Structured Content 与 Content List V1/V2 九种输出,各入口暴露各自的导出子集,详见[输出格式与结果契约](https://opendatalab.github.io/MinerU/zh/reference/output_files/)。
    - 结果携带带版本号的共享 schema;PDF 页范围(`1-5,8,r3-r1`,`r1` 为最后一页,`all` 表示整本)在 CLI、文档库、API 与 SDK 间行为一致。

  - 破坏性变更与迁移
    - 入口变化:`mineru -p input.pdf -o output` 变为 `mineru parse input.pdf --pages all -o output.md`(文档库)或 `mineru-kit parse input.pdf -o output.md`(一次性转换);`mineru-gradio` 变为 `mineru-webui`;`-m all` 变为 `mineru-kit models download --tier standard`。
    - 依赖分组:`mineru[core]`、`mineru[pipeline]` 等 extras 调整为基础包、`mineru[torch]`、`mineru[full]`;Python 要求 `>=3.10,<3.15`。
    - 配置迁移至 `$MINERU_HOME/config.yaml`,不再读取旧的 `mineru.json`。
    - 旧版结果 JSON 仅在 Doclib 缓存读取边界内自动转换,其余场景请重新解析源文档。
    - 既有的 AMD 及厂商加速卡适配仍停留在 `mineru<4`。
    - 完整变化清单请参考 [3.x → 4.0 迁移指南](https://opendatalab.github.io/MinerU/zh/reference/migration_4/)。

  在 4.0 版本,MinerU 从文档转换工具升级为隐私优先的文档平台:分档解析质量、原生多格式解析、面向 Agent 的可检索本地文档库与稳定引用定位,以及统一的接口体系。欢迎从[快速开始](https://opendatalab.github.io/MinerU/zh/quick_start/)、[档位与运行时](https://opendatalab.github.io/MinerU/zh/usage/tiers/)与 [SDK 与 API](https://opendatalab.github.io/MinerU/zh/usage/sdk_api/) 入手,完整版本历史见 [changelog](https://opendatalab.github.io/MinerU/zh/reference/changelog/)。

**Full Changelog**: https://github.com/opendatalab/MinerU/compare/mineru-3.4.5-released...mineru-4.0.0-released

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