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MODEL Listed

OmniParser

OmniParser is a specialized vision-language model from Microsoft designed to bridge the gap between raw visual input and structured semantic data. Unlike general-purpose multimodal models that often struggle with precise spatial reasoning, OmniParser focuses on parsing complex UI elements, icons, and text layouts from screenshots. For developers building autonomous agents, RPA tools, or accessibility software, this model provides a critical layer of perception by converting unstructured pixels into actionable, machine-readable coordinates and descriptions. It excels at identifying interactive components within a GUI, making it an essential component for agentic workflows where the model must 'see' and interact with software interfaces. Integration is straightforward via Hugging Face, and its MIT license makes it highly suitable for both research and commercial deployment in automated testing or computer-use environments.

microsoftimage text to text
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01 / MODEL CARD

Model card

OmniParser is a specialized vision-language model from Microsoft designed to bridge the gap between raw visual input and structured semantic data. Unlike general-purpose multimodal models that often struggle with precise spatial reasoning, OmniParser focuses on parsing complex UI elements, icons, and text layouts from screenshots. For developers building autonomous agents, RPA tools, or accessibility software, this model provides a critical layer of perception by converting unstructured pixels into actionable, machine-readable coordinates and descriptions. It excels at identifying interactive components within a GUI, making it an essential component for agentic workflows where the model must 'see' and interact with software interfaces. Integration is straightforward via Hugging Face, and its MIT license makes it highly suitable for both research and commercial deployment in automated testing or computer-use environments.

Model typeimage text to text
Providermicrosoft
Licensemit
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/microsoft/OmniParser
View model source
Version informationUse the source repository for the latest version
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03 / DOWNLOAD

Download this model

We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.

This entry points to Hugging Face. The commands use the matching ModelScope repository format; confirm that the repository exists on ModelScope before running them. Model repository: microsoft/OmniParser
Install ModelScope

Install the CLI and SDK dependency before downloading.

pip install modelscope
Download the full model repository

Download the complete weights, configuration and model card.

modelscope download --model microsoft/OmniParser
Download one file to a local directory

README.md is used as an example; replace it with another repository file when needed.

modelscope download --model microsoft/OmniParser README.md --local_dir ./dir
Download with the SDK

Useful in Python projects and automation scripts.

from modelscope import snapshot_download
model_dir = snapshot_download('microsoft/OmniParser')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/microsoft/OmniParser.git
Clone without downloading LFS blobs

Fetch the repository structure first, then pull large files when needed.

GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/microsoft/OmniParser.git
04 / WORKFLOW

How to use

  1. 01
    Step 1

    Read the model card and source information.

  2. 02
    Step 2

    Start with a small, non-sensitive evaluation.

  3. 03
    Step 3

    Review quality, licensing and usage limits.

  4. 04
    Step 4

    Adopt it only after validation.

05 / DISCUSSIONS

Discussions

Use this space to keep checking source information, usage experience and maintenance status.

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