gemma-4-26B-A4B

gemma-4-26B-A4B

Reads text and images and writes text, for developers who want an open-weights Google DeepMind model for coding, reasoning and image questions on their own GPU or workstation.

Made by google on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

About

What it is: Gemma 4 26B A4B is one size in the open Gemma 4 family from Google DeepMind. It reads text and images and writes text, using a Mixture-of-Experts design. The repository holds about 25.8B parameters as Safetensors files for the transformers library.

Who it suits: It suits developers and researchers who want an open-weights model for text generation, coding, reasoning and image understanding, run on a consumer GPU or a workstation.

Title: Who uses this model
Industry | Who uses it | How they use it | Example
Software | Developers | Add coding help and reasoning to their own apps | Ask it to review a function
Research | Machine learning researchers | Study an open Mixture-of-Experts model | Compare it with the dense sizes in the family
Product teams | Agent builders | Build assistants that call functions | Give the model a tool and let it decide when to use it

Anyone who needs audio input can skip this size, since the card lists audio only for the E2B, E4B and 12B models.

Where to use it:

• Python scripts that use the transformers library
• A consumer GPU or a workstation
• Windows, macOS or Linux with Python, for downloading the files

Title: Jobs it does
Use case | Who | What they get back
Text generation | Writers and developers | Written replies to a prompt
Coding help | Developers | Code and explanations in text
Image questions | Anyone with pictures to check | Text answers about an image you supply
Reasoning | Researchers | Step-by-step answers, with thinking modes you can configure

How to set it up: You need Python and enough disk space. The BF16 files weigh about 51.6 GB, and a 4-bit copy is estimated at about 12.9 GB.

• Python with pip
• The huggingface_hub package
• Free disk space for the weights

1. Install huggingface_hub.
2. Run the download command to save the model files on your computer.
3. Load the files with the transformers library in your own script.

pip install -U huggingface_hub
hf download google/gemma-4-26B-A4B

How to use it: Load the downloaded files with transformers and give the model text, or an image together with text. The system role lets you set ground rules for a conversation. The card says thinking modes are configurable and points to its own pages for the exact settings.

Example: You hand the model a photo of a chart and ask for the main trend in two sentences. It answers in text. A system message can tell it to keep replies short and formal.

For newcomers and experts: Think of it as a model that looks at a picture and a question, then writes an answer. A first small test is one image and one short question. The family also has smaller sizes if this one is too big for your computer.

Underneath, attention layers alternate between a local sliding window and full global attention, and the last layer is always global. Global layers share keys and values and use Proportional RoPE to save memory on long contexts. The Mixture-of-Experts design trades a larger file for cheaper work per token.

Text or image goes in
Hybrid attention layers
Mixture-of-Experts blocks
Text comes out

Good to know: The family reaches a context window of 256K tokens and supports more than 140 languages. Other people have published 35 quantized and 91 fine-tuned versions of this model. The release has pre-trained and instruction-tuned variants, so check the repository name to see which one you get.

Title: Estimated weight size
BF16: 51.6 GB
4-bit: 12.9 GB

• License: Apache 2.0.
• Cost to run: none named.
• Data it reaches: the files come from Hugging Face, and the model then runs on your own hardware.
• Not for: audio input at this size, which the card lists only for E2B, E4B and 12B.

On Hugging Face, 13 November 2026

• Task: image text to text
• Library: transformers
• Parameters: 25.8B
• Weights: about 51.6 GB in BF16; about 12.9 GB at 4-bit (estimate)
• Formats: Safetensors
• Downloads in the last 30 days: 74,790
• Likes: 470
• License: apache-2.0
• Quantized versions: 37
• Fine-tunes: 92
• Tags: transformers, safetensors, gemma4, image-text-to-text

Links

• Model: https://huggingface.co/google/gemma-4-26B-A4B
• Files: https://huggingface.co/google/gemma-4-26B-A4B/tree/main

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download google/gemma-4-26B-A4B

Then follow the usage in its model card. Nothing in this kit runs by itself.