--- title: "gemma-4-12b-it-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/5c808b31-349e-4069-ad4e-f80ffc3a1bee" updated: "2026-11-12" --- # gemma-4-12b-it-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Unsloth's GGUF quantized copy of Google's instruction-tuned Gemma 4 12B, a model that takes text, images, audio and video and writes text, for running locally. gemma-4-12b-it-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by unsloth ## About ### What it is gemma-4-12b-it-GGUF is a GGUF copy of google/gemma-4-12B-it, made by Unsloth. The base is the Gemma 4 12B Unified model from Google DeepMind. The record lists 11.9B parameters, and the 4-bit weights come to about 6 GB by its estimate. The model takes text, images, audio and video as input and writes text. The card says it understands audio and vision directly, without separate encoders. ### Who it suits It suits people who want a multimodal model on their own computer and have a machine that can hold a file of about 6 GB. Developers can also fine-tune it, as the card mentions Unsloth Studio for that. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a local model for text, image and audio input | Asking what a screenshot shows | | Agents | Tool builders | Use function calling and thinking modes | A helper that picks a tool for a request | | Media | Editors | Get text answers about clips and recordings | Summarizing a short recording | | Research | Hobbyist researchers | Try a recent open model on their own hardware | Comparing it with smaller Gemma 4 sizes | Skip it if you want a hosted assistant and have no plan to run a model. ### Where to use it - Local apps that load GGUF files - Unsloth Studio, which the card says can run and fine-tune this model - Windows, macOS or Linux, with Python for the download step | Use case | Who | What they get back | | --- | --- | --- | | Chat and reasoning | Developers | Text answers, with configurable thinking modes | | Image and audio questions | App builders | Text answers about a picture or a recording | | Function calling | Agent builders | Calls to tools driven by the model | ### How to set it up You need a few things in place first. - Python and pip, for the download command - A local app that can load GGUF files - About 6 GB of free disk space for the 4-bit weights, by the record's estimate 1. Install the Hugging Face hub package with pip. 2. Download the repository with the hf command. 3. Load the GGUF file in your local app. Unsloth keeps a guide for running Gemma 4 12B. ```sh pip install -U huggingface_hub hf download unsloth/gemma-4-12b-it-GGUF ``` ### How to use it After loading the file, you chat with the model and may add images or audio. The card says Gemma 4 supports a system role for more controllable conversations and native function calling. It also lists multi-token prediction support through an Unsloth guide. ### Example You load the file and give the model a screenshot with the question "What does this error message mean?" The model reads the picture and answers in text. ### For newcomers and experts Start with one short text question. When that works, add an image. Audio and video come last, since they need more setup in the app you use. The 12B Unified model reads audio and images without separate encoders. That makes the model encoder-free and keeps its size friendly to consumer hardware. Gemma 4 attention mixes local sliding windows with global layers, and the family reaches a context window of 256K tokens. The quantized copy trades some precision for a smaller file. Download the GGUF file with hf → Load it in a local app → Send text, an image or audio → The model writes text back ### Good to know - License: Apache 2.0 - Cost to run: none named, but you need a machine with room for about 6 GB of weights - Data it reaches: it downloads files from Hugging Face onto your computer ## README ````markdown # gemma-4-12b-it-GGUF Unsloth's GGUF quantized copy of Google's instruction-tuned Gemma 4 12B, a model that takes text, images, audio and video and writes text, for running locally. 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: gemma-4-12b-it-GGUF is a GGUF copy of google/gemma-4-12B-it, made by Unsloth. The base is the Gemma 4 12B Unified model from Google DeepMind. The record lists 11.9B parameters, and the 4-bit weights come to about 6 GB by its estimate. The model takes text, images, audio and video as input and writes text. The card says it understands audio and vision directly, without separate encoders. Who it suits: It suits people who want a multimodal model on their own computer and have a machine that can hold a file of about 6 GB. Developers can also fine-tune it, as the card mentions Unsloth Studio for that. ```table Industry | Who uses it | How they use it | Example Software | Developers | Run a local model for text, image and audio input | Asking what a screenshot shows Agents | Tool builders | Use function calling and thinking modes | A helper that picks a tool for a request Media | Editors | Get text answers about clips and recordings | Summarizing a short recording Research | Hobbyist researchers | Try a recent open model on their own hardware | Comparing it with smaller Gemma 4 sizes ``` Skip it if you want a hosted assistant and have no plan to run a model. Where to use it: - Local apps that load GGUF files - Unsloth Studio, which the card says can run and fine-tune this model - Windows, macOS or Linux, with Python for the download step ```table Use case | Who | What they get back Chat and reasoning | Developers | Text answers, with configurable thinking modes Image and audio questions | App builders | Text answers about a picture or a recording Function calling | Agent builders | Calls to tools driven by the model ``` How to set it up: You need a few things in place first. - Python and pip, for the download command - A local app that can load GGUF files - About 6 GB of free disk space for the 4-bit weights, by the record's estimate 1. Install the Hugging Face hub package with pip. 2. Download the repository with the hf command. 3. Load the GGUF file in your local app. Unsloth keeps a guide for running Gemma 4 12B. ```sh pip install -U huggingface_hub hf download unsloth/gemma-4-12b-it-GGUF ``` How to use it: After loading the file, you chat with the model and may add images or audio. The card says Gemma 4 supports a system role for more controllable conversations and native function calling. It also lists multi-token prediction support through an Unsloth guide. Example: You load the file and give the model a screenshot with the question "What does this error message mean?" The model reads the picture and answers in text. For newcomers and experts: Start with one short text question. When that works, add an image. Audio and video come last, since they need more setup in the app you use. The 12B Unified model reads audio and images without separate encoders. That makes the model encoder-free and keeps its size friendly to consumer hardware. Gemma 4 attention mixes local sliding windows with global layers, and the family reaches a context window of 256K tokens. The quantized copy trades some precision for a smaller file. ```flow Download the GGUF file with hf Load it in a local app Send text, an image or audio The model writes text back ``` Good to know: - License: Apache 2.0 - Cost to run: none named, but you need a machine with room for about 6 GB of weights - Data it reaches: it downloads files from Hugging Face onto your computer ## On Hugging Face, 13 November 2026 - Task: image text to text - Parameters: 11.9B - Weights: about 6 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 2,534,530 - Likes: 963 - License: apache-2.0 - Based on: google/gemma-4-12B-it - Quantized versions: 1 - Tags: gguf, gemma4, unsloth, gemma, google, gemma4_unified, image-text-to-text, conversational ## Links - Model: https://huggingface.co/unsloth/gemma-4-12b-it-GGUF - Files: https://huggingface.co/unsloth/gemma-4-12b-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-4-12b-it-GGUF ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [unsloth/gemma-4-12b-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-4-12b-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-4-12b-it-GGUF (this page) | 2,534,530 | 963 | 11.9B | apache-2.0 | 2026-07-17 | | [gemma-4-E4B-it-GGUF](https://mindket.com/p/fa9df3ff-5b05-4e15-984f-04ccfc125e3e) | 702,365 | 687 | 7.5B | apache-2.0 | 2026-07-17 | | [gemma-4-E2B-it-GGUF](https://mindket.com/p/be304d82-a02d-4163-94a6-2fab2d7a7210) | 674,565 | 356 | 4.6B | apache-2.0 | 2026-07-17 | | [gemma-4-31B-it-GGUF](https://mindket.com/p/f257bf61-ef21-40bb-9e67-e4d77bf5e0e0) | 428,266 | 677 | 30.7B | apache-2.0 | 2026-07-17 | | [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-qat-GGUF](https://mindket.com/p/97ef5b61-d969-4212-aa91-1789e4ce409f) | 196,871 | 617 | 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 · rahimnathwani · 2026-07-21](https://news.ycombinator.com/item?id=48986520): Nativ: Run frontier open models locally on your Mac: brew install llama.cpp llama-server -hf unsloth/gemma-4-12b-it-GGUF:UD-Q8\_K\_XL - [Bluesky · デイリーHuggingFaceトレンド · 2026-06-08](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mnrtzcgrwb26): 今日のHuggingFaceトレンド unsloth/gemma-4-12b-it-GGUF Google DeepMindが開発したマルチモーダルオープンモデルGemma 4の配布を目的としています。 テキスト、画像、音声、ビデオの入力を処理してテキストを出力でき、エンコーダフリーな設計により消費者向けデバイスでのローカル実行が可能です。 テキスト生成やコーディング、推論などのタスクに対応し、多言語サポートと最大256Kトークンのコンテキストウィンドウを備えています。 - [Hacker News · lambda · 2026-06-03](https://news.ycombinator.com/item?id=48388663): Gemma 4 12B: A unified, encoder-free multimodal model: It's not? There's an mmproj in the GGUFs released by ggml-org: https://huggingface.co/ggml-org/gemma-4-12B-it-GGUF/tree/mai... From the visual guide, there's still the 35M parameter embedder, then the linear projector, for vision, and the linear projector for audio, so it does have some parameters… - [Bluesky · デイリーHuggingFaceトレンド · 2026-06-10](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mnwr23t5mm2i): 今日のHuggingFaceトレンド unsloth/gemma-4-12b-it-GGUF Google DeepMindが開発したオープンウェイトのマルチモーダルモデルGemma 4 12Bを提供することを目的としています。 テキスト、画像、音声、動画の入力を処理し、テキストを出力します。 エンコーダー不要な設計により、PCやスマートフォンなどのローカル環境で動作し、テキスト生成やコーディング、推論などのタスクに利用可能です。 - [Bluesky · デイリーHuggingFaceトレンド · 2026-06-06](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mnmk52q5ns2f): 今日のHuggingFaceトレンド unsloth/gemma-4-12b-it-GGUF Google DeepMindが開発したオープンモデルGemma 4の12Bモデルを提供するためのリポジトリです。 テキスト、画像、音声、ビデオを入力として処理し、テキストを出力するマルチモーダル機能を提供します。 エンコーダー不要の設計により、消費者向けデバイスなどのローカル環境での効率的な実行が可能で、テキスト生成やコーディング、推論などのタスクに利用されます。 - [Bluesky · ほしけん · 2026-06-04](https://bsky.app/profile/hosiken.jp/post/3mngpbamegc2b): 今日リリースされたローカルLLMのGoogle Gemma 4 12B 日本語が怪しいとか壊れているとか言われてますが、 Windows の LM Studio だと、lmstudio-community/gemma-4-12B-it-GGUF なら特に問題なかった。 Unsloth や ggml-org だと日本語以前にそもそも回答時エラーになって動かなかった - [Bluesky · デイリーHuggingFaceトレンド · 2026-06-04](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mnhnnaroom2j): 今日のHuggingFaceトレンド unsloth/gemma-4-12b-it-GGUF Google DeepMindが開発したオープンウェイトのマルチモーダルモデルGemma 4を提供するためのリポジトリです。 テキスト、画像、音声、ビデオなどの入力を処理し、テキストを出力します。 エンコーダー不要の統合設計により、消費者向けデバイスを含むローカル環境で効率的に動作させることを目的としています。 - [Bluesky · probbrain.com · 2026-06-04](https://bsky.app/profile/probbrain.bsky.social/post/3mngkaxbcfw2h): unsloth/gemma-4-12b-it-GGUF · 134♥ · 0 dl ## 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: 2026-07-17 - First published: 2026-05-29 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open unsloth/gemma-4-12b-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-4-12b-it-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/5c808b31-349e-4069-ad4e-f80ffc3a1bee) - [Its page on Mindket](https://mindket.com/p/5c808b31-349e-4069-ad4e-f80ffc3a1bee)