NVIDIA Nemotron Parse 1.1

摘要

我们推出Nemotron-Parse-1.1，这是一款轻量级文档解析与OCR模型，其在前代Nemoretriever-Parse-1.0的基础上实现了能力升级。该模型在通用OCR、Markdown格式解析、结构化表格解析以及图片/图表/示意图的文本提取方面均表现出增强性能，同时支持对视觉密集文档进行更长输出序列的处理。与前代模型一致，它能够提取文本段的边界框及对应语义类别。Nemotron-Parse-1.1采用编码器-解码器架构，参数量达8.85亿（其中语言解码器为紧凑型2.56亿参数），在公开基准测试中达到业界领先的准确率，成为强有力的轻量级OCR解决方案。我们已在Huggingface平台公开发布模型权重、优化的NIM容器以及作为Nemotron-VLM-v2数据集组成部分的部分训练数据。此外，我们还发布了Nemotron-Parse-1.1-TC版本，该版本通过缩减视觉标记长度实现20%的速度提升，且质量损失微乎其微。

English

We introduce Nemotron-Parse-1.1, a lightweight document parsing and OCR model that advances the capabilities of its predecessor, Nemoretriever-Parse-1.0. Nemotron-Parse-1.1 delivers improved capabilities across general OCR, markdown formatting, structured table parsing, and text extraction from pictures, charts, and diagrams. It also supports a longer output sequence length for visually dense documents. As with its predecessor, it extracts bounding boxes of text segments, as well as corresponding semantic classes. Nemotron-Parse-1.1 follows an encoder-decoder architecture with 885M parameters, including a compact 256M-parameter language decoder. It achieves competitive accuracy on public benchmarks making it a strong lightweight OCR solution. We release the model weights publicly on Huggingface, as well as an optimized NIM container, along with a subset of the training data as part of the broader Nemotron-VLM-v2 dataset. Additionally, we release Nemotron-Parse-1.1-TC which operates on a reduced vision token length, offering a 20% speed improvement with minimal quality degradation.