--- title: "gemma-4-E2B-it-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/be304d82-a02d-4163-94a6-2fab2d7a7210" updated: "2026-11-13" --- # gemma-4-E2B-it-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Unsloth's GGUF files of Google DeepMind's Gemma 4 E2B instruction-tuned model, which takes text and images and writes text, with a 128K context. For people who run models locally on laptops and small machines. gemma-4-E2B-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 Unsloth's GGUF files of gemma-4-E2B-it, an instruction-tuned model from Google DeepMind's Gemma 4 family. Gemma 4 models are multimodal, taking text and images as input and writing text. Audio is supported on the small models. The Hugging Face record lists 4.6B parameters and about 2.3 GB at 4-bit. ### Who it suits People who want a small multimodal model they can run on their own laptop or edge device, and developers who need reasoning, coding or function calling in a compact model. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers on small machines | Run a multimodal model locally | Ask questions about a screenshot | | Agents | Builders of tool-using agents | Use native function calling | Let the model call a weather or search function | | On-device apps | Teams shipping to laptops and phones | Keep inference on the device | Answer a user's question with no server call | You can skip it if you need the biggest Gemma 4 sizes, since the family also has 26B A4B and 31B versions. ### Where to use it - Unsloth Studio, which the card says can run and fine-tune Gemma 4 - llama.cpp and other GGUF-based tools - Windows, macOS or Linux with Python, to download the files | Use case | Who | What they get back | | --- | --- | --- | | Image questions | App developers | Text answers about an image | | Coding help | Developers | Code and explanations | | Tool-calling agents | Agent builders | Function calls from the model's native support | | Structured chat | Prompt writers | Replies shaped by a system prompt | ### How to set it up You need a GGUF-capable tool and enough memory for a roughly 2.3 GB file at 4-bit. The card points to Unsloth's guide for running Gemma 4, and it notes a re-download for the latest chat template. - Python and pip - A GGUF-capable runtime such as llama.cpp or Unsloth Studio - Disk space for the file you choose 1. Download the GGUF files. 2. Open the guide the card links for run steps. 3. Load a file in your chosen tool. ```sh pip install -U huggingface_hub hf download unsloth/gemma-4-E2B-it-GGUF ``` ### How to use it Load the model in your tool, then chat with text or images. Gemma 4 supports the system role, so you can set the behavior in a system prompt. Thinking modes can be configured. ### Example You attach a photo of a receipt and ask, "What is the total?". The model replies with the amount as text. The card does not show a sample output in the part used here. ### For newcomers and experts If you are new, try it in Unsloth Studio, where the card says the model runs with tool calling. Start with a short text question before you add images. For experts, Gemma 4 spans dense and mixture-of-experts designs in four sizes: E2B, E4B, 26B A4B and 31B. The small models have a 128K context window and the medium ones 256K. Unsloth later added MTP support and updated the files for Google's latest chat template. Text or image input → Gemma 4 E2B, quantized to GGUF → Text output ### Good to know - Family sizes: E2B, E4B, 26B A4B and 31B - Context: 128K tokens for the small models - Updates: re-download for the latest chat template and llama.cpp fixes - License: Apache 2.0 - Cost to run: no API key or paid service named - Data it reaches: downloads files from Hugging Face, nothing else is named - Not for: the card names no limits, and the output is text only ## README ````markdown # gemma-4-E2B-it-GGUF Unsloth's GGUF files of Google DeepMind's Gemma 4 E2B instruction-tuned model, which takes text and images and writes text, with a 128K context. For people who run models locally on laptops and small machines. 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 Unsloth's GGUF files of gemma-4-E2B-it, an instruction-tuned model from Google DeepMind's Gemma 4 family. Gemma 4 models are multimodal, taking text and images as input and writing text. Audio is supported on the small models. The Hugging Face record lists 4.6B parameters and about 2.3 GB at 4-bit. Who it suits: People who want a small multimodal model they can run on their own laptop or edge device, and developers who need reasoning, coding or function calling in a compact model. ```table Industry | Who uses it | How they use it | Example Software | Developers on small machines | Run a multimodal model locally | Ask questions about a screenshot Agents | Builders of tool-using agents | Use native function calling | Let the model call a weather or search function On-device apps | Teams shipping to laptops and phones | Keep inference on the device | Answer a user's question with no server call ``` You can skip it if you need the biggest Gemma 4 sizes, since the family also has 26B A4B and 31B versions. Where to use it: - Unsloth Studio, which the card says can run and fine-tune Gemma 4 - llama.cpp and other GGUF-based tools - Windows, macOS or Linux with Python, to download the files ```table Use case | Who | What they get back Image questions | App developers | Text answers about an image Coding help | Developers | Code and explanations Tool-calling agents | Agent builders | Function calls from the model's native support Structured chat | Prompt writers | Replies shaped by a system prompt ``` How to set it up: You need a GGUF-capable tool and enough memory for a roughly 2.3 GB file at 4-bit. The card points to Unsloth's guide for running Gemma 4, and it notes a re-download for the latest chat template. - Python and pip - A GGUF-capable runtime such as llama.cpp or Unsloth Studio - Disk space for the file you choose 1. Download the GGUF files. 2. Open the guide the card links for run steps. 3. Load a file in your chosen tool. ```sh pip install -U huggingface_hub hf download unsloth/gemma-4-E2B-it-GGUF ``` How to use it: Load the model in your tool, then chat with text or images. Gemma 4 supports the system role, so you can set the behavior in a system prompt. Thinking modes can be configured. Example: You attach a photo of a receipt and ask, "What is the total?". The model replies with the amount as text. The card does not show a sample output in the part used here. For newcomers and experts: If you are new, try it in Unsloth Studio, where the card says the model runs with tool calling. Start with a short text question before you add images. For experts, Gemma 4 spans dense and mixture-of-experts designs in four sizes: E2B, E4B, 26B A4B and 31B. The small models have a 128K context window and the medium ones 256K. Unsloth later added MTP support and updated the files for Google's latest chat template. ```flow Text or image input Gemma 4 E2B, quantized to GGUF Text output ``` Good to know: - Family sizes: E2B, E4B, 26B A4B and 31B - Context: 128K tokens for the small models - Updates: re-download for the latest chat template and llama.cpp fixes - License: Apache 2.0 - Cost to run: no API key or paid service named - Data it reaches: downloads files from Hugging Face, nothing else is named - Not for: the card names no limits, and the output is text only ## On Hugging Face, 13 November 2026 - Task: image text to text - Parameters: 4.6B - Weights: about 2.3 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 674,565 - Likes: 356 - License: apache-2.0 - Based on: google/gemma-4-E2B-it - Quantized versions: 5 - Fine-tunes: 2 - Tags: gguf, gemma4, unsloth, gemma, google, image-text-to-text, conversational ## Links - Model: https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF - Files: https://huggingface.co/unsloth/gemma-4-E2B-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-E2B-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-E2B-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-4-E2B-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-E2B-it-GGUF (this page) | 674,565 | 356 | 4.6B | 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 | | [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-4-31B-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. - [Bluesky · Alfonso² Peterssen · 2026-04-07](https://bsky.app/profile/mukel.bsky.social/post/3miw5hbead22j): Strong with the JVM, Gemma 4 is 😌 jbang gemma4@mukel \\ --model %{https://hf.co/unsloth/gemma-4-E2B-it-GGUF/resolve/main/gemma-4-E2B-it-Q8\_0.gguf} \\ --system-prompt "like Master Yoda, reply you must" \\ --chat \~5GB once, download you must. Python or CUDA, you need not. Local AI, this is. ## 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: 2026-04-01 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open unsloth/gemma-4-E2B-it-GGUF on Hugging Face](https://huggingface.co/unsloth/gemma-4-E2B-it-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/be304d82-a02d-4163-94a6-2fab2d7a7210) - [Its page on Mindket](https://mindket.com/p/be304d82-a02d-4163-94a6-2fab2d7a7210)