--- title: "Qwen3.8-27B-GGUF by ggml-org" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/720a742a-d997-4f75-b282-2b5e0f48204f" updated: "2026-11-12" --- # Qwen3.8-27B-GGUF by ggml-org > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs Qwen3.8-27B, a 26.9B model that takes images and text and replies in text, as a GGUF file for local use through the llama tools. Made for people who want it on their own computer. Qwen3.8-27B-GGUF by ggml-org is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by ggml-org ## About ### What it is This is a GGUF copy of Qwen3.8-27B, a model that takes images and text and answers in text. ggml-org made it with an automatic conversion step. Hugging Face estimates the weights at about 13.4 GB at 4-bit, and the page itself holds little beyond the run steps. ### Who it suits It suits people who want to try a 26.9B image-and-text model on their own machine through the llama tools. Who uses this model | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Serve a local model that reads images and text | Start the serve command and send it a question | | Research | Machine learning hobbyists | Test how a 26.9B model behaves in GGUF form | Compare it with other quantized copies | | Education | Students | Learn how local model serving works | Run the serve command and chat with the model | If you need a documented model with benchmarks, you can skip it, because the page says little about the model. ### Where to use it - The Llama app - A terminal, with the llama serve command - Windows, macOS or Linux with Python, for downloading the files Jobs it does | Use case | Who | What they get back | | --- | --- | --- | | Local chat | Anyone with a capable computer | Text replies from a model running on their own machine | | Image questions | Developers | Text answers about pictures they provide | | File download | Tinkerers | The GGUF files saved to a local folder | ### How to set it up You need a way to run the model and enough disk space for it. - The Llama app, or the llama command in a terminal - Python with pip, if you only want the files - Room for roughly 13.4 GB of weights, which is an estimate 1. Get the Llama app or make sure the llama command works in your terminal. 2. Run the serve command with the repository name, and the model loads from it. 3. To only save the files, install huggingface\_hub and run the download command instead. ```bash llama serve -hf ggml-org/Qwen3.8-27B-GGUF ``` ```bash pip install -U huggingface_hub hf download ggml-org/Qwen3.8-27B-GGUF ``` ### How to use it Start the serve command and the model comes up from the repository it names. The Llama app does the same job without a terminal. The download command saves the files if you prefer to keep a local copy. Main commands | Tool | What it does | | --- | --- | | llama serve | Starts the model from the repository named in the command | | hf download | Saves the repository's files to your computer | ### Example You start the model with the serve command, then give it a screenshot and ask what it shows. As an image-and-text model, it is meant to answer in plain text. ### For newcomers and experts A model like this reads a picture plus a question and writes back an answer. The easiest first step is the Llama app, which runs it without any commands. If you prefer a terminal, the serve command does the same. GGUF is a single-file format for running models locally. Storing weights at 4-bit trades some precision for a smaller download, and the 13.4 GB figure is Hugging Face's estimate. The base model is Qwen/Qwen3.8-27B, and the card also lists a second source model named Qwen3.8-27B-DFlash2 by incoai. Qwen3.8-27B base model → Automatic GGUF conversion → ggml-org repository → llama serve or the Llama app → Local replies in text ### Good to know The card is short and carries a to-do note for more information, so it gives no benchmarks or usage limits. Four quantized versions by other people exist, and none are fine-tunes. - 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 computer. - Not for: the card names no restrictions, so check the original Qwen model page before relying on it. ## README ````markdown # Qwen3.8-27B-GGUF by ggml-org Runs Qwen3.8-27B, a 26.9B model that takes images and text and replies in text, as a GGUF file for local use through the llama tools. Made for people who want it on their own computer. 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: This is a GGUF copy of Qwen3.8-27B, a model that takes images and text and answers in text. ggml-org made it with an automatic conversion step. Hugging Face estimates the weights at about 13.4 GB at 4-bit, and the page itself holds little beyond the run steps. Who it suits: It suits people who want to try a 26.9B image-and-text model on their own machine through the llama tools. ```table Title: Who uses this model Industry | Who uses it | How they use it | Example Software | Developers | Serve a local model that reads images and text | Start the serve command and send it a question Research | Machine learning hobbyists | Test how a 26.9B model behaves in GGUF form | Compare it with other quantized copies Education | Students | Learn how local model serving works | Run the serve command and chat with the model ``` If you need a documented model with benchmarks, you can skip it, because the page says little about the model. Where to use it: - The Llama app - A terminal, with the llama serve command - Windows, macOS or Linux with Python, for downloading the files ```table Title: Jobs it does Use case | Who | What they get back Local chat | Anyone with a capable computer | Text replies from a model running on their own machine Image questions | Developers | Text answers about pictures they provide File download | Tinkerers | The GGUF files saved to a local folder ``` How to set it up: You need a way to run the model and enough disk space for it. - The Llama app, or the llama command in a terminal - Python with pip, if you only want the files - Room for roughly 13.4 GB of weights, which is an estimate 1. Get the Llama app or make sure the llama command works in your terminal. 2. Run the serve command with the repository name, and the model loads from it. 3. To only save the files, install huggingface_hub and run the download command instead. ```bash llama serve -hf ggml-org/Qwen3.8-27B-GGUF ``` ```bash pip install -U huggingface_hub hf download ggml-org/Qwen3.8-27B-GGUF ``` How to use it: Start the serve command and the model comes up from the repository it names. The Llama app does the same job without a terminal. The download command saves the files if you prefer to keep a local copy. ```table Title: Main commands Tool | What it does llama serve | Starts the model from the repository named in the command hf download | Saves the repository's files to your computer ``` Example: You start the model with the serve command, then give it a screenshot and ask what it shows. As an image-and-text model, it is meant to answer in plain text. For newcomers and experts: A model like this reads a picture plus a question and writes back an answer. The easiest first step is the Llama app, which runs it without any commands. If you prefer a terminal, the serve command does the same. GGUF is a single-file format for running models locally. Storing weights at 4-bit trades some precision for a smaller download, and the 13.4 GB figure is Hugging Face's estimate. The base model is Qwen/Qwen3.8-27B, and the card also lists a second source model named Qwen3.8-27B-DFlash2 by incoai. ```flow Qwen3.8-27B base model Automatic GGUF conversion ggml-org repository llama serve or the Llama app Local replies in text ``` Good to know: The card is short and carries a to-do note for more information, so it gives no benchmarks or usage limits. Four quantized versions by other people exist, and none are fine-tunes. - 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 computer. - Not for: the card names no restrictions, so check the original Qwen model page before relying on it. ## On Hugging Face, 13 November 2026 - Task: image text to text - Parameters: 26.9B - Weights: about 13.4 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,000,687 - Likes: 157 - License: apache-2.0 - Based on: Qwen/Qwen3.8-27B - Quantized versions: 4 - Tags: gguf, quantized, image-text-to-text, conversational ## Links - Model: https://huggingface.co/ggml-org/Qwen3.8-27B-GGUF - Files: https://huggingface.co/ggml-org/Qwen3.8-27B-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/Qwen3.8-27B-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/Qwen3.8-27B-GGUF on Hugging Face](https://huggingface.co/ggml-org/Qwen3.8-27B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3.8-27B-GGUF by ggml-org (this page) | 1,000,687 | 157 | 26.9B | apache-2.0 | 2026-11-12 | | [MiniCPM-V-4.7-1B-gguf](https://mindket.com/p/f793ef5c-72e1-400b-91fa-5b2c31b01f3f) | 168,636 | 114 | 1B | apache-2.0 | 2026-11-11 | | [Clef-GGUF](https://mindket.com/p/784cbfd1-ad94-4593-9a6f-42a6a8650f64) | 20,883 | 30 | 27B | apache-2.0 | 2026-11-12 | | [Unlimited-OCR-2-GGUF](https://mindket.com/p/0d8a371b-6f90-4b59-8dd6-b520e35b577b) | 8,452 | 8 | 2.9B | mit | 2026-11-01 | | [Arete-27B-GGUF](https://mindket.com/p/587591c7-2295-48cc-8bfc-5d3fd980cbfc) | 1,933 | 15 | 26.9B | apache-2.0 | 2026-11-08 | | [DeepSeek-V4.1-Flash-1017 GGUF](https://mindket.com/p/213b01c3-a7f9-4409-94e7-6c7a5e8c9979) | 1,408 | 3 | 748B | mit | 2026-11-11 | 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 · pi-victor · 2026-08-23](https://news.ycombinator.com/item?id=49408368): I gave Qwen 3.8 27B a reverse-engineering job and it finished in 30 minutes: i'm not good with paper work, in fact, i'm horrible with anything that's paperwork related. for the past few days, i ran this model on my rtx 4090 + rtx 3070 and told it to check all the bills, invoices, contracts for me and my small company. i used pi with llama and the pi-llama plugin. oh, boy -… - [Hacker News · lelandbatey · 2026-08-14](https://news.ycombinator.com/item?id=49303788): Qwen 3.8 27B: I can get 128k context on a 5070ti with 16 GB of VRAM (using the Unsloth 2-bit quant0). This is via a .bat file on Windows 11. I'm getting about 50-60 tokens/second and the quality is much higher than Qwen 3.6 27B. I'm using llama.cpp1: llama-server.exe ^ -m "Qwen3.8-27B-UD-Q2\_K\_XL.gguf" ^… ## 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: 2026-08-14 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open ggml-org/Qwen3.8-27B-GGUF on Hugging Face](https://huggingface.co/ggml-org/Qwen3.8-27B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/720a742a-d997-4f75-b282-2b5e0f48204f) - [Its page on Mindket](https://mindket.com/p/720a742a-d997-4f75-b282-2b5e0f48204f)