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MODEL Listed

gemma-4-31B-it-assistant

The Gemma 4 31B-it-assistant is a high-parameter, instruction-tuned model designed for complex, multimodal workflows. Unlike standard text-only LLMs, this 'any-to-any' architecture allows developers to build applications that seamlessly process and reason across diverse data modalities. At 31B parameters, it strikes a strategic balance between high-level reasoning capabilities and deployment efficiency, making it suitable for edge-cloud hybrid architectures or high-throughput local inference. For developers, the primary value lies in its versatility: you can leverage it for sophisticated cross-modal retrieval, complex instruction following, and integrated multimodal reasoning tasks. Released under the Apache 2.0 license, it offers the flexibility needed for commercial integration without the constraints of restrictive proprietary licenses. Whether you are building advanced agents or multimodal RAG pipelines, this model provides a robust foundation for non-linear data processing.

googleany to any
01 / MODEL CARD

Model card

The Gemma 4 31B-it-assistant is a high-parameter, instruction-tuned model designed for complex, multimodal workflows. Unlike standard text-only LLMs, this 'any-to-any' architecture allows developers to build applications that seamlessly process and reason across diverse data modalities. At 31B parameters, it strikes a strategic balance between high-level reasoning capabilities and deployment efficiency, making it suitable for edge-cloud hybrid architectures or high-throughput local inference. For developers, the primary value lies in its versatility: you can leverage it for sophisticated cross-modal retrieval, complex instruction following, and integrated multimodal reasoning tasks. Released under the Apache 2.0 license, it offers the flexibility needed for commercial integration without the constraints of restrictive proprietary licenses. Whether you are building advanced agents or multimodal RAG pipelines, this model provides a robust foundation for non-linear data processing.

Model typeany to any
Providergoogle
Licenseapache-2.0
02 / FILES & VERSIONS

Model files and versions

Model cardModel description and metadata available in this entry
Listed
Source repositoryhttps://huggingface.co/google/gemma-4-31B-it-assistant
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: google/gemma-4-31B-it-assistant
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 google/gemma-4-31B-it-assistant
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 google/gemma-4-31B-it-assistant 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('google/gemma-4-31B-it-assistant')
Clone with Git

Make sure Git LFS is installed correctly.

git lfs install
git clone https://www.modelscope.cn/google/gemma-4-31B-it-assistant.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/google/gemma-4-31B-it-assistant.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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