--- title: "gemma-3-12b-it-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/8ca21838-e184-4d92-b58a-0cdc0acd6909" updated: "2026-11-13" --- # gemma-3-12b-it-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Answers questions and summarizes text, and reads images, from GGUF files of Google's Gemma 3 12B instruction model. It suits people who want to run it on their own computer. gemma-3-12b-it-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by unsloth ## About ### What it is This repository holds GGUF files of gemma-3-12b-it, the instruction-tuned 12B model in Google DeepMind's Gemma 3 family, packaged by unsloth. The model takes text and images as input and writes text as output. The card says it fits tasks such as question answering, summarizing and reasoning. ### Who it suits It suits people who want a mid-size model that reads both text and pictures and runs on their own machine, and developers who then fine-tune or build on it. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run an image and text model locally inside an app | A developer sends a screenshot and a question and shows the text answer | | Research | Analysts | Summarize long documents using the large context window | An analyst pastes a long report and asks for the main findings | | Education | Students and teachers | Ask questions about diagrams and reading material | A student sends a photo of a diagram and asks what it shows | If you want a hosted chat service with nothing to download, you can skip it. ### Where to use it - Tools that read GGUF files, such as llama.cpp and Ollama, which the page names for exporting models - Your own Windows, macOS or Linux computer, after downloading the files with Python - Cloud servers you run yourself, which the card says suit models of this size | Use case | Who | What they get back | | --- | --- | --- | | Question answering | Anyone | A text answer to a typed question | | Summarizing documents | Analyst | A shorter text version of a long input | | Image questions | Developer or student | A text description or analysis of a picture | ### How to set it up - Python on your computer, to run pip and the Hugging Face tools - Disk space, about 5.9 GB for a 4-bit copy by Hugging Face's estimate - A runner that loads GGUF files 1. Install the Hugging Face hub package. 2. Download the repository files. 3. Load a GGUF file in your runner. The card gives no run command of its own and points to the unsloth guide for running Gemma 3. ```sh pip install -U huggingface_hub hf download unsloth/gemma-3-12b-it-GGUF ``` ### How to use it You type a prompt, or send an image with a question, and the model writes text back. The card says each image is resized to 896 by 896 and turned into 256 tokens, and that the model accepts up to 128K tokens of input. The only command shown is the download step. ```sh hf download unsloth/gemma-3-12b-it-GGUF ``` | Tool | What it does | | --- | --- | | hf download | Fetches the repository files to your computer | | pip install -U huggingface\_hub | Installs the package that provides the hf command | ### Example You send a chart image along with the question, "What does this chart show?" The model reads the picture and replies in text with a description and its main points. ### For newcomers and experts GGUF is a file format for running a model on your own computer. The model reads both words and pictures and answers in words. A small first step is to download the files, open one in a GGUF-capable app and ask a short question. For experts, this is a 12B model from Google DeepMind, with 11.8B parameters by Hugging Face's count, and a 128K token context. Images are normalized to 896 by 896 and encoded into 256 tokens each. The unsloth page also covers fine-tuning Gemma 3 with its own notebooks and exporting the result to GGUF or Ollama. Google DeepMind releases Gemma 3 12B instruction model → unsloth packages it as GGUF files → You download the files with hf → A runner loads one file → It reads text and images and writes text ### Good to know - Size: 11.8B parameters, about 5.9 GB at 4-bit by Hugging Face's estimate - Context: up to 128K tokens of input for the 12B size - Languages: the card says over 140, while Hugging Face lists English - License: the Gemma license, so read its terms of use - Cost to run: none named, apart from your own hardware - Data it reaches: downloading uses the web and writes files to your disk, and the source names no other access - Not for: anything the Gemma terms of use rule out, since the page names no other limits ## README ````markdown # gemma-3-12b-it-GGUF Answers questions and summarizes text, and reads images, from GGUF files of Google's Gemma 3 12B instruction model. It suits people who want to run it on their own computer. Made by unsloth 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: This repository holds GGUF files of gemma-3-12b-it, the instruction-tuned 12B model in Google DeepMind's Gemma 3 family, packaged by unsloth. The model takes text and images as input and writes text as output. The card says it fits tasks such as question answering, summarizing and reasoning. Who it suits: It suits people who want a mid-size model that reads both text and pictures and runs on their own machine, and developers who then fine-tune or build on it. ```table Industry | Who uses it | How they use it | Example Software | Developers | Run an image and text model locally inside an app | A developer sends a screenshot and a question and shows the text answer Research | Analysts | Summarize long documents using the large context window | An analyst pastes a long report and asks for the main findings Education | Students and teachers | Ask questions about diagrams and reading material | A student sends a photo of a diagram and asks what it shows ``` If you want a hosted chat service with nothing to download, you can skip it. Where to use it: - Tools that read GGUF files, such as llama.cpp and Ollama, which the page names for exporting models - Your own Windows, macOS or Linux computer, after downloading the files with Python - Cloud servers you run yourself, which the card says suit models of this size ```table Use case | Who | What they get back Question answering | Anyone | A text answer to a typed question Summarizing documents | Analyst | A shorter text version of a long input Image questions | Developer or student | A text description or analysis of a picture ``` How to set it up: - Python on your computer, to run pip and the Hugging Face tools - Disk space, about 5.9 GB for a 4-bit copy by Hugging Face's estimate - A runner that loads GGUF files 1. Install the Hugging Face hub package. 2. Download the repository files. 3. Load a GGUF file in your runner. The card gives no run command of its own and points to the unsloth guide for running Gemma 3. ```sh pip install -U huggingface_hub hf download unsloth/gemma-3-12b-it-GGUF ``` How to use it: You type a prompt, or send an image with a question, and the model writes text back. The card says each image is resized to 896 by 896 and turned into 256 tokens, and that the model accepts up to 128K tokens of input. The only command shown is the download step. ```sh hf download unsloth/gemma-3-12b-it-GGUF ``` ```table Tool | What it does hf download | Fetches the repository files to your computer pip install -U huggingface_hub | Installs the package that provides the hf command ``` Example: You send a chart image along with the question, "What does this chart show?" The model reads the picture and replies in text with a description and its main points. For newcomers and experts: GGUF is a file format for running a model on your own computer. The model reads both words and pictures and answers in words. A small first step is to download the files, open one in a GGUF-capable app and ask a short question. For experts, this is a 12B model from Google DeepMind, with 11.8B parameters by Hugging Face's count, and a 128K token context. Images are normalized to 896 by 896 and encoded into 256 tokens each. The unsloth page also covers fine-tuning Gemma 3 with its own notebooks and exporting the result to GGUF or Ollama. ```flow Google DeepMind releases Gemma 3 12B instruction model unsloth packages it as GGUF files You download the files with hf A runner loads one file It reads text and images and writes text ``` Good to know: - Size: 11.8B parameters, about 5.9 GB at 4-bit by Hugging Face's estimate - Context: up to 128K tokens of input for the 12B size - Languages: the card says over 140, while Hugging Face lists English - License: the Gemma license, so read its terms of use - Cost to run: none named, apart from your own hardware - Data it reaches: downloading uses the web and writes files to your disk, and the source names no other access - Not for: anything the Gemma terms of use rule out, since the page names no other limits ## On Hugging Face, 13 November 2026 - Task: image text to text - Library: transformers - Parameters: 11.8B - Weights: about 5.9 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 84,937 - Likes: 204 - License: gemma - Languages: en - Based on: google/gemma-3-12b-it - Tags: transformers, gguf, gemma3, image-text-to-text, unsloth, gemma, google, conversational ## Links - Model: https://huggingface.co/unsloth/gemma-3-12b-it-GGUF - Files: https://huggingface.co/unsloth/gemma-3-12b-it-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download unsloth/gemma-3-12b-it-GGUF ``` 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 [unsloth/gemma-3-12b-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-3-12b-it-GGUF) ## 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-3-12b-it-GGUF (this page) | 84,937 | 204 | 11.8B | gemma | 2025-08-14 | | [gemma-3-4b-it-GGUF](https://mindket.com/p/643c26b6-4129-4e6b-93c1-b35450442bc5) | 160,720 | 216 | 3.9B | gemma | 2025-08-14 | | [gemma-3-27b-it-GGUF](https://mindket.com/p/92fcdbbc-a9e1-4d36-a8b5-90224a919f74) | 50,284 | 211 | 27B | gemma | 2025-08-14 | | [gemma-3-270m-it-GGUF](https://mindket.com/p/87dfd2c3-99d8-46f6-b32a-d49c2830280f) | 91,489 | 181 | 268M | gemma | 2025-08-15 | | [gemma-4-31B-it-qat-GGUF](https://mindket.com/p/808c5b4b-b27d-43fd-bf03-d1970ccfbce4) | 79,933 | 226 | 30.7B | apache-2.0 | 2026-07-17 | | [gemma-4-12b-it-GGUF](https://mindket.com/p/5c808b31-349e-4069-ad4e-f80ffc3a1bee) | 2,534,530 | 963 | 11.9B | apache-2.0 | 2026-07-17 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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 · danielhanchen · 2025-05-10](https://news.ycombinator.com/item?id=43943370): Vision Now Available in Llama.cpp: It works super well\! You'll have to compile llama.cpp from source, and you should get a llama-mtmd-cli program. I made some quants with vision support - literally run: ./llama.cpp/llama-mtmd-cli -hf unsloth/gemma-3-4b-it-GGUF:Q4\_K\_XL -ngl -1 ./llama.cpp/llama-mtmd-cli -hf… ## 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: 2025-08-14 - First published: 2025-03-12 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open unsloth/gemma-3-12b-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-3-12b-it-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/8ca21838-e184-4d92-b58a-0cdc0acd6909) - [Its page on Mindket](https://mindket.com/p/8ca21838-e184-4d92-b58a-0cdc0acd6909)