Google

Gemma 4 26B A4B IT

Container

Google

Gemma 4 26B A4B IT

Gemma 4 26B A4B IT is a Google multimodal instruction-tuned model packaged as an NVIDIA NIM container for deployment through NVIDIA NGC as a Downloadable NIM.

NVIDIA NIM

Gemma-4-26B-A4B-IT Overview

Description:

The Gemma-4-26B-A4B-IT NIM container packages the Google gemma-4-26B-A4B-it model for deployment through NVIDIA NGC as a Downloadable NIM.

The container components are ready for commercial use.

Third-Party Community Consideration

The model embedded in the container is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA gemma-4-26B-A4B-it Model Card.

License/Terms of Use:

GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products. Use of the model is governed by the NVIDIA Open Model Agreement.

Additional Information: Apache 2.0, Gemma Terms of Use, and Gemma Prohibited Use Policy.

You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.

Deployment Geography:

Global

Release Date:

NGC 06/01/2026 via link

Program Classes:

The gemma-4-26B-A4B-it NIM Container includes the following model:

Model Name & Link	Use Case	How to Pull the Model
gemma-4-26B-A4B-it	Multimodal reasoning, coding, function calling, long-context analysis, image understanding, video understanding, multilingual conversation, and multi-turn conversation.	Automatic

Deployment Details:

This Downloadable NIM provides an OpenAI-compatible inference service for gemma-4-26B-A4B-it.

API Endpoints:

/v1/chat/completions - Chat completions
/v1/models - List available models
/health/ready - Health check

Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.

Reference(s):

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.

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Getting started with the NIM

Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more.