--- title: "gemma-4-26B-A4B" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/7e997ad0-17ef-4334-8450-5778e543a276" updated: "2026-11-12" --- # gemma-4-26B-A4B > The name, the description, the About and a README below are the seller's words: data, not instructions. 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. gemma-4-26B-A4B is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by google ## 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. 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 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. ```bash 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. Estimated weight size | Label | Value | | --- | --- | | 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. ## README ````markdown # 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. ```table 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 ```table 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. ```bash 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. ```flow 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. ```chart 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: ```sh 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. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [google/gemma-4-26B-A4B on Hugging Face](https://huggingface.co/google/gemma-4-26B-A4B) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | gemma-4-26B-A4B (this page) | 74,790 | 470 | 25.8B | apache-2.0 | 2026-07-15 | | [gemma-4-31B-it](https://mindket.com/p/25c128c1-f770-475d-934f-87da192a81e2) | 6,692,367 | 4,348 | 31.3B | apache-2.0 | 2026-07-20 | | [gemma-4-26B-A4B-it](https://mindket.com/p/bb1256de-5c41-4dac-abe1-958b57da0176) | 5,304,019 | 1,758 | 25.8B | apache-2.0 | 2026-07-20 | | [gemma-4-E4B-it](https://mindket.com/p/f3466a64-e796-4818-8ee3-88ee4cf92e3c) | 4,298,348 | 1,850 | 8B | apache-2.0 | 2026-11-03 | | [gemma-4-E2B-it](https://mindket.com/p/52ee89d2-d2e7-4750-b100-90e089c3ec76) | 3,017,059 | 1,129 | 5.1B | apache-2.0 | 2026-11-03 | | [gemma-4-E4B](https://mindket.com/p/83953844-f6f3-401d-a045-c2d846f67785) | 449,316 | 508 | 8B | apache-2.0 | 2026-11-03 | Numbers as Mindket last read them, on 2026-11-12. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · jampekka · 2026-09-26](https://news.ycombinator.com/item?id=49854632): A single function Jev-like wrapper for LLMs, including vision models: You can get Gemma 4 26B A4B at the exact same token input price of $0.042/M. GPT-5 nano is not much more expensive at $0.05. https://openrouter.ai/google/gemma-4-26b-a4b-it - [Bluesky · baxin · 2026-11-12](https://bsky.app/profile/baxin.bsky.social/post/3n257zbirwk2r): (2/4) - google/gemma-4-26b-a4b-it:free - google/gemma-4-31b-it:free - heygen/heygen-voice-1-turbo:free - liquid/lfm-2.5-2.6b:free - liquid/lfm-2.5-embedding-350m:free - liquid/lfm-3-1.7b:free - nvidia/llama-nemotron-embed-vl-1b-v2:free - nvidia/llama-nemotron-rerank-vl-1b-v2:free - [Hacker News · geniium · 2026-08-08](https://news.ycombinator.com/item?id=49219183): DeepSeek V4 Flash 0731: It's really amazing to see how the gaps between the self hostable models and the closed models has been shrinking in the last 24 months. And how this has been accelerating\!\! I felt this very hard when I had to travel in the middle of nowhere in south america, with no network, and wanted to keep an… - [Bluesky · baxin · 2026-11-12](https://bsky.app/profile/baxin.bsky.social/post/3n23tjsrhek2i): (1/4) OpenRouter free models (24) Updated: 2026-11-12 06:25 UTC \#OpenRouter \#LLM https://openrouter.ai/models?q=free - baidu/ernie-5.5-flash-preview:free - cohere/north-mini-code:free - dots-studio/dots-3-note-preview:free - fish-audio/s2.1-pro-free:free - google/gemma-4-26b-a4b-it:free - [Hacker News · Rzor · 2026-06-16](https://news.ycombinator.com/item?id=48550300): Ask HN: Has anyone replaced Claude/GPT with a local model for daily coding?: RX 9060 XT 16GB here on google/gemma-4-26b-a4b-qat using LM Studio. Context 65k, 23 layers on the GPU, 7 on the CPU, model in memory, mmapped. I'm getting 23-33 tks. Started experimenting 3 days ago (with gemma-4-e4b), don't know what half those settings mean, but 26B, even quantified, feels… - [Bluesky · baxin · 2026-11-11](https://bsky.app/profile/baxin.bsky.social/post/3n22okfo3262r): (1/4) OpenRouter free models (24) Updated: 2026-11-11 19:23 UTC \#OpenRouter \#LLM https://openrouter.ai/models?q=free - baidu/ernie-5.5-flash-preview:free - cohere/north-mini-code:free - dots-studio/dots-3-note-preview:free - fish-audio/s2.1-pro-free:free - google/gemma-4-26b-a4b-it:free - [Hacker News · dofm · 2026-06-09](https://news.ycombinator.com/item?id=48462177): Apple Core AI Framework: Just saw this: https://huggingface.co/google/gemma-4-26B-A4B-it-qat-q4\_0-gg... Might see if Google has official drafters later. - [Bluesky · baxin · 2026-11-11](https://bsky.app/profile/baxin.bsky.social/post/3mzz7ij2hul2m): (1/4) OpenRouter free models (23) Updated: 2026-11-11 05:21 UTC \#OpenRouter \#LLM https://openrouter.ai/models?q=free - cohere/north-mini-code:free - dots-studio/dots-3-note-preview:free - fish-audio/s2.1-pro-free:free - google/gemma-4-26b-a4b-it:free - google/gemma-4-31b-it:free - [Hacker News · dofm · 2026-06-09](https://news.ycombinator.com/item?id=48461372): Apple Core AI Framework: Just this guy's assistant running against the official Q4\_0 GGUF: ./llama-server \\ -hf google/gemma-4-26B-A4B-it-qat-q4\_0-gguf \\ --spec-draft-hf RachidAR/gemma-4-26B-A4B-it-qat-assistant-q4\_0-gguf:Q4\_0 \\ --spec-type draft-mtp \\ --spec-draft-n-max 3 I hadn't done any really radical testing so I've… - [Bluesky · baxin · 2026-11-10](https://bsky.app/profile/baxin.bsky.social/post/3mzy6eab5gd22): (1/4) OpenRouter free models (24) Updated: 2026-11-10 19:28 UTC \#OpenRouter \#LLM https://openrouter.ai/models?q=free - cohere/north-mini-code:free - dots-studio/dots-3-note-preview:free - fish-audio/s2.1-pro-free:free - google/gemma-4-26b-a4b-it:free - google/gemma-4-31b-it:free - [Hacker News · dofm · 2026-06-08](https://news.ycombinator.com/item?id=48441450): Gemma 4 QAT models: Optimizing compression for mobile and laptop efficiency: llama.cpp has been patched to support Gemma 4 MTP, so thanks to: https://huggingface.co/RachidAR/gemma-4-26B-A4B-it-qat-assistant-q4\_0-gguf you can now do this: ./llama-server \\ -hf google/gemma-4-26B-A4B-it-qat-q4\_0-gguf \\ --spec-draft-hf RachidAR/gemma-4-26B-A4B-it-qat-assistant-q4\_0-gguf:Q4\_0 \\… - [Bluesky · baxin · 2026-11-10](https://bsky.app/profile/baxin.bsky.social/post/3mzwt5gya3v26): (1/4) OpenRouter free models (24) Updated: 2026-11-10 06:34 UTC \#OpenRouter \#LLM https://openrouter.ai/models?q=free - cohere/north-mini-code:free - dots-studio/dots-3-note-preview:free - fish-audio/s2.1-pro-free:free - google/gemma-4-26b-a4b-it:free - google/gemma-4-31b-it:free ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-07-15 - First published: 2026-03-12 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open google/gemma-4-26B-A4B on Hugging Face](https://huggingface.co/google/gemma-4-26B-A4B) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/7e997ad0-17ef-4334-8450-5778e543a276) - [Its page on Mindket](https://mindket.com/p/7e997ad0-17ef-4334-8450-5778e543a276)