Merge pull request #5109 from myhloli/dev

feat: update changelog for 3.3.0 release with Hybrid parsing optimizations and VLM model upgrades

README.md

@@ -80,6 +80,25 @@ Domestic AI chips: Ascend · Cambricon · Enflame · MetaX · Moore Threads · K
 
 # Changelog
 
+- 2026/06/11 3.3.0 Released
+
+  This release focuses on **Hybrid parsing performance optimization** and **VLM model capability upgrades**. The main updates include:
+
+  - New `effort` parsing-strength parameter for the Hybrid backend
+    - Added two parsing-strength levels, `medium` and `high`, allowing users to balance parsing speed, parsing accuracy, and feature requirements.
+    - On OmniDocBench v1.6, `medium` reduces overall accuracy by only `0.13` points compared with `high`, while delivering `35%` ~ `220%` parsing speed improvements across different devices and scenarios:
+      - Linux: about `80%` faster for text PDF scenarios and about `35%` faster for OCR scenarios
+      - Windows: about `90%` faster for text PDF scenarios and about `45%` faster for OCR scenarios
+      - macOS: about `220%` faster for text PDF scenarios and about `50%` faster for OCR scenarios
+    - The default Hybrid backend now uses `effort=medium`, significantly improving overall parsing efficiency while maintaining high parsing accuracy.
+    - The `medium` level does not support `image analysis`; for maximum parsing accuracy or `image analysis` support, switch to the high-strength parsing mode with `effort=high`, which may have an impact on parsing speed.
+
+  - VLM model upgraded to `MinerU2.5-Pro-2605-1.2B`
+    - Fixed multiple model issues found in the `2604` version, further improving parsing stability on complex documents.
+    - Added native multilingual OCR support, reducing the need for extra language-parameter configuration and improving out-of-the-box usability for multilingual documents.
+
+  With the 3.3.0 release, MinerU further improves Hybrid backend efficiency across platforms and scenarios while maintaining high-accuracy parsing. The default `medium` effort level is better suited for most day-to-day document processing tasks, while `high` is designed for scenarios that require maximum parsing accuracy or `image analysis` capabilities.
+
 - 2026/04/18 3.1.0 Released
 
   This release focuses on **licensing openness, parsing accuracy, and full-format native support**. The main updates include:

README_zh-CN.md

@@ -79,6 +79,25 @@ MCP Server · LangChain / Dify / FastGPT 原生集成 · 10+ 国产算力适配
 
 # 更新记录
 
+- 2026/06/11 3.3.0 发布
+
+  本次版本更新聚焦于 **Hybrid 解析性能优化** 与 **VLM 模型能力升级**。主要更新内容包括：
+
+  - Hybrid 后端新增 `effort` 解析强度参数
+    - 新增 `medium` 与 `high` 两档解析强度，用户可根据解析速度、解析精度和功能需求灵活选择。
+    - 在 OmniDocBench v1.6 评测中，`medium` 相比 `high` 综合精度仅降低 `0.13`，但在不同设备和场景下可获得 `35%` ~ `220%` 的解析速度提升：
+      - Linux：文本 PDF 场景提升约 `80%`，OCR 场景提升约 `35%`
+      - Windows：文本 PDF 场景提升约 `90%`，OCR 场景提升约 `45%`
+      - macOS：文本 PDF 场景提升约 `220%`，OCR 场景提升约 `50%`
+    - 默认 Hybrid 后端将使用 `effort=medium`，在保持高解析精度的同时显著提升整体解析效率。
+    - `medium` 档不支持 `image analysis`（图片/图表分析）功能；如需极致解析精度或启用 `image analysis`，可通过 `effort=high` 切换至高强度解析模式，但解析速度会受到一定影响。
+
+  - VLM 模型升级至 `MinerU2.5-Pro-2605-1.2B`
+    - 修复 `2604` 版本中存在的多处模型问题，进一步提升复杂文档场景下的解析稳定性。
+    - 原生支持多语言 OCR，降低多语言文档解析时对额外语言参数配置的依赖，提升跨语言场景的开箱即用体验。
+
+  通过 3.3.0 版本，MinerU 在保持高精度解析能力的同时，进一步提升了 Hybrid 后端在多平台、多场景下的解析效率。默认 `medium` 解析强度更适合大多数日常文档处理任务，而 `high` 模式则面向对解析精度和 `image analysis` 能力有更高要求的场景。
+
 - 2026/04/18 3.1.0 发布
 
   本次版本更新聚焦于**许可协议开放性、解析精度提升与全格式原生支持**。主要更新内容包括：