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AIモデルライブラリ/zenosai/MonkeyOCRv2-B-Parsing
モデル情報

MonkeyOCRv2-B-Parsing

zenosai · MonkeyOCRv2-B-Parsing

* `2026.09.07` 🚀 MonkeyOCRv2-Parsing is now supported by RAGFlow as a PDF parser. Thanks to the RAGFlow team and community for the support! * `2026.08.22` 🖥️ We now support running MonkeyOCRv2-Parsing on CPU. See the CPU support instructions. * `2026.08.17` ⚡ Releasing training and evaluation instructions for Recognition, Detection, Overlapping Text Segmentation and Formula. * `2026.07.24` ⚡ We released MonkeyOCRv2-B-Parsing-DFlash, enabling vLLM serving with DFlash for up to 2× faster inference. * `2026.07.22` 🏆 MonkeyOCRv2-B-Parsing ranks #1 among evaluated open-source models on the official MDPBench Leaderboard, achieving 83.3 overall across 17 languages, including digital-born and photographed documents. * `2026.07.21` 📦 We release MonkeyDoc v2, an open multilingual corpus for document-oriented pretraining. We hope it can serve as a shared data foundation for more transparent, reproducible, and fair comparisons in Document AI. * `2026.07.14` 🚀 We release MonkeyOCRv2, including MonkeyOCRv2 vision encoder, MonkeyOCRv2-Parsing for multilingual document parsing, MonkeyOCRv2-Und for efficient document understanding. MonkeyOCRv2 is released as a standalone, document-native vision encoder. It can be integrated into different OCR and document AI systems as a visual backbone. The current release has been evaluated on document parsing, document understanding, text recognition, formula recognition, text detection, document tampering detection, and overlapping-text segmentation.

翻訳待ちのため原文を表示しています。

画像質問応答license:apache-2.0
コンテキスト長非公開
入力 → 出力テキスト、画像 → テキスト
モデルウェイト未確認
情報更新日時2026/11/2 19:17:16
OVERVIEW

モデル紹介

* `2026.09.07` 🚀 MonkeyOCRv2-Parsing is now supported by RAGFlow as a PDF parser. Thanks to the RAGFlow team and community for the support! * `2026.08.22` 🖥️ We now support running MonkeyOCRv2-Parsing on CPU. See the CPU support instructions. * `2026.08.17` ⚡ Releasing training and evaluation instructions for Recognition, Detection, Overlapping Text Segmentation and Formula. * `2026.07.24` ⚡ We released MonkeyOCRv2-B-Parsing-DFlash, enabling vLLM serving with DFlash for up to 2× faster inference. * `2026.07.22` 🏆 MonkeyOCRv2-B-Parsing ranks #1 among evaluated open-source models on the official MDPBench Leaderboard, achieving 83.3 overall across 17 languages, including digital-born and photographed documents. * `2026.07.21` 📦 We release MonkeyDoc v2, an open multilingual corpus for document-oriented pretraining. We hope it can serve as a shared data foundation for more transparent, reproducible, and fair comparisons in Document AI. * `2026.07.14` 🚀 We release MonkeyOCRv2, including MonkeyOCRv2 vision encoder, MonkeyOCRv2-Parsing for multilingual document parsing, MonkeyOCRv2-Und for efficient document understanding. MonkeyOCRv2 is released as a standalone, document-native vision encoder. It can be integrated into different OCR and document AI systems as a visual backbone. The current release has been evaluated on document parsing, document understanding, text recognition, formula recognition, text detection, document tampering detection, and overlapping-text segmentation.

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

PRICING & COST

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

出典・チャネル入力出力課金単位収集日時
確認可能な料金がありません。出典を確認してください。

月額の基本トークン費用を試算

—

試算はキャッシュ割引、段階料金、マルチモーダル追加料金、検索、税金、追加推論出力を含みません。

INDEPENDENT BENCHMARKS

公開評価と実行設定

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

収録済みの全ランキング →

よくある質問

オープンウェイトなら無料で商用利用できますか？

必ずしもそうではありません。バージョン別のライセンス、商用条件、利用方針を確認してください。自前運用には計算資源と保守費用も必要です。

これはリアルタイムの請求料金ですか？

収集日時付きの料金スナップショットです。最新のバージョン、地域、割引、課金方式は各チャネルで確認してください。

出典と追跡記録

huggingface · zenosai/MonkeyOCRv2-B-Parsing ↗2026/10/29 04:13:44
huggingface · enrich:b8c6acb4-e492-4852-864d-32ddb9739f32 ↗2026/10/29 00:12:11

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。