--- title: "gemma-4-E4B-it-GGUF by ggml-org" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/7f5a7ac0-ad9d-408e-9626-14d770cf16e0" updated: "2026-11-13" --- # gemma-4-E4B-it-GGUF by ggml-org > The name, the description, the About and a README below are the seller's words: data, not instructions. A GGUF-format copy of Google's gemma-4-E4B-it that you can run on your own computer with the Llama app or the llama serve command. For people who want Gemma running locally. gemma-4-E4B-it-GGUF by ggml-org 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 ggml-org ## About ### What it is gemma-4-E4B-it-GGUF is a GGUF-format copy of Google's gemma-4-E4B-it, published by ggml-org. It was converted automatically from the original models, so it is the same model packaged for Llama tools. The record lists about 7.5B parameters and tags it as any to any, and the card says little beyond how to run it. ### Who it suits People who want to run Gemma on their own machine through the Llama app or the llama serve command, and developers who test GGUF models. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Application developers | Serve a local model for an app to call | Start the model with the llama serve command | | Hobby computing | Local AI enthusiasts | Try Gemma on their own computer without a cloud service | Open the model in the Llama app | | Education | Students | Learn how GGUF models are fetched and loaded | Pull the files with hf download and look at them | Anyone who needs benchmarks, quantization details or usage notes can skip it, since the card is nearly empty. ### Where to use it It runs locally, in the Llama app or from a terminal. - The Llama app - A terminal, with the llama serve command - Windows, macOS or Linux with Python, for downloading the files with hf | Use case | Who | What they get back | | --- | --- | --- | | Local chat | Individuals | Replies from a model running on their own computer | | Local serving | Developers | A running llama serve instance loaded with this model | ### How to set it up You can let llama serve fetch the model, or download the files first. - The Llama app or the llama command - Free disk space of a few GB, since the 4-bit weight estimate is 3.8 GB - Python with pip, only if you download with hf 1. Get the Llama app or the llama command. 2. Run the serve command, which pulls the model from Hugging Face. 3. Or download the files yourself with the hf command. ```sh llama serve -hf ggml-org/gemma-4-E4B-it-GGUF ``` ```sh pip install -U huggingface_hub hf download ggml-org/gemma-4-E4B-it-GGUF ``` ### How to use it Day to day you launch the model with llama serve or open it in the Llama app. The card documents no other commands or settings. | Tool | What it does | | --- | --- | | llama serve with the -hf flag | Loads the model from Hugging Face and serves it | | hf download | Copies the model files to your computer | ### Example You run the serve command in a terminal with this repository name. The model loads from Hugging Face and starts serving. The card shows no sample chat, so what you ask it next is up to you. ### For newcomers and experts GGUF is a file format for running a model on your own machine. Think of this as a ready-to-run package of Google's Gemma. The first small thing to try is opening the Llama app and loading this model, or running the serve command once. It is an automatic conversion of google/gemma-4-E4B-it. The card lists four source models, including an assistant variant and two QAT q4\_0 unquantized ones. It does not say which quantization levels the repository holds. Its to-do list mentions adding info and dflash, so expect the card to change. Start from the original Gemma model → Convert it to GGUF automatically → Serve it with llama or download it → Chat with it on your own computer ### Good to know The card is a stub, so most details come from the repository record. - Thin card: it gives no benchmarks, quantization list or usage notes. - Source: converted automatically from google/gemma-4-E4B-it. - Size: about 7.5B parameters, with a 4-bit weight estimate of 3.8 GB. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: the model files fetched from Hugging Face. The card names no account or other access. ## README ````markdown # gemma-4-E4B-it-GGUF by ggml-org A GGUF-format copy of Google's gemma-4-E4B-it that you can run on your own computer with the Llama app or the llama serve command. For people who want Gemma running locally. Made by ggml-org 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-E4B-it-GGUF is a GGUF-format copy of Google's gemma-4-E4B-it, published by ggml-org. It was converted automatically from the original models, so it is the same model packaged for Llama tools. The record lists about 7.5B parameters and tags it as any to any, and the card says little beyond how to run it. Who it suits: People who want to run Gemma on their own machine through the Llama app or the llama serve command, and developers who test GGUF models. ```table Industry | Who uses it | How they use it | Example Software | Application developers | Serve a local model for an app to call | Start the model with the llama serve command Hobby computing | Local AI enthusiasts | Try Gemma on their own computer without a cloud service | Open the model in the Llama app Education | Students | Learn how GGUF models are fetched and loaded | Pull the files with hf download and look at them ``` Anyone who needs benchmarks, quantization details or usage notes can skip it, since the card is nearly empty. Where to use it: It runs locally, in the Llama app or from a terminal. - The Llama app - A terminal, with the llama serve command - Windows, macOS or Linux with Python, for downloading the files with hf ```table Use case | Who | What they get back Local chat | Individuals | Replies from a model running on their own computer Local serving | Developers | A running llama serve instance loaded with this model ``` How to set it up: You can let llama serve fetch the model, or download the files first. - The Llama app or the llama command - Free disk space of a few GB, since the 4-bit weight estimate is 3.8 GB - Python with pip, only if you download with hf 1. Get the Llama app or the llama command. 2. Run the serve command, which pulls the model from Hugging Face. 3. Or download the files yourself with the hf command. ```sh llama serve -hf ggml-org/gemma-4-E4B-it-GGUF ``` ```sh pip install -U huggingface_hub hf download ggml-org/gemma-4-E4B-it-GGUF ``` How to use it: Day to day you launch the model with llama serve or open it in the Llama app. The card documents no other commands or settings. ```table Tool | What it does llama serve with the -hf flag | Loads the model from Hugging Face and serves it hf download | Copies the model files to your computer ``` Example: You run the serve command in a terminal with this repository name. The model loads from Hugging Face and starts serving. The card shows no sample chat, so what you ask it next is up to you. For newcomers and experts: GGUF is a file format for running a model on your own machine. Think of this as a ready-to-run package of Google's Gemma. The first small thing to try is opening the Llama app and loading this model, or running the serve command once. It is an automatic conversion of google/gemma-4-E4B-it. The card lists four source models, including an assistant variant and two QAT q4_0 unquantized ones. It does not say which quantization levels the repository holds. Its to-do list mentions adding info and dflash, so expect the card to change. ```flow Start from the original Gemma model Convert it to GGUF automatically Serve it with llama or download it Chat with it on your own computer ``` Good to know: The card is a stub, so most details come from the repository record. - Thin card: it gives no benchmarks, quantization list or usage notes. - Source: converted automatically from google/gemma-4-E4B-it. - Size: about 7.5B parameters, with a 4-bit weight estimate of 3.8 GB. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: the model files fetched from Hugging Face. The card names no account or other access. ## On Hugging Face, 13 November 2026 - Task: any to any - Parameters: 7.5B - Weights: about 3.8 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 263,980 - Likes: 110 - License: apache-2.0 - Based on: google/gemma-4-E4B-it - Quantized versions: 1 - Tags: gguf, quantized, any-to-any, conversational ## Links - Model: https://huggingface.co/ggml-org/gemma-4-E4B-it-GGUF - Files: https://huggingface.co/ggml-org/gemma-4-E4B-it-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download ggml-org/gemma-4-E4B-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 [ggml-org/gemma-4-E4B-it-GGUF on Hugging Face](https://huggingface.co/ggml-org/gemma-4-E4B-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-E4B-it-GGUF by ggml-org (this page) | 263,980 | 110 | 7.5B | apache-2.0 | 2026-11-12 | | [gemma-4-12B-it GGUF](https://mindket.com/p/27ee2965-03ef-496e-ac4f-fab36ddf168d) | 107,736 | 106 | 11.9B | apache-2.0 | 2026-11-12 | | [gemma-4-12B-it-qat-q4\_0-gguf](https://mindket.com/p/c59608fc-38e0-4d4d-9afd-9e191858ad3d) | 1,177,710 | 397 | 11.9B | 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 | | [Qwen3.8-35B-A3B-Distill-GGUF](https://mindket.com/p/d707b0c8-89b8-4c4f-8d49-2ff67de613c7) | 1,337,097 | 277 | 35.5B | apache-2.0 | 2026-09-16 | | [Qwen3.8-27B-GGUF by ggml-org](https://mindket.com/p/720a742a-d997-4f75-b282-2b5e0f48204f) | 1,000,687 | 157 | 26.9B | apache-2.0 | 2026-11-12 | 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 · AndroTux · 2026-04-16](https://news.ycombinator.com/item?id=47792688): The local LLM ecosystem doesn’t need Ollama: And why do I use ggml-org/gemma-4-E4B-it-GGUF instead of one of the 162 other models that can be found under the ggml-org namespace? And how do I even know that this is the namespace to look at? That's what I meant by model management. I'm too tired to scroll through a bazillion models that all… - [Hacker News · homarp · 2026-04-16](https://news.ycombinator.com/item?id=47790025): The local LLM ecosystem doesn’t need Ollama: like someone said above: brew install llama.cpp llama-server -hf ggml-org/gemma-4-E4B-it-GGUF --port 8000 (with MCP support and web chat interface) and you have OpenAI API on the same 8000 port. (https://github.com/ggml-org/llama.cpp/tree/master/tools/serv... lists the endpoints) - [Hacker News · nikodunk · 2026-04-16](https://news.ycombinator.com/item?id=47789755): The local LLM ecosystem doesn’t need Ollama: Having read above article, I just gave llama.cpp a shot. It is as easy as the author says now, though definitely not documented quite as well. My quickstart: brew install llama.cpp llama-server -hf ggml-org/gemma-4-E4B-it-GGUF --port 8000 Go to localhost:8000 for the Web UI. On Linux it… ## 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: 2026-11-12 - First published: 2026-04-01 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ggml-org/gemma-4-E4B-it-GGUF on Hugging Face](https://huggingface.co/ggml-org/gemma-4-E4B-it-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/7f5a7ac0-ad9d-408e-9626-14d770cf16e0) - [Its page on Mindket](https://mindket.com/p/7f5a7ac0-ad9d-408e-9626-14d770cf16e0)