--- title: "Qwen3.5-0.8B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/9d6a62e8-addb-4de1-9bf9-7cfc58c2bab9" updated: "2026-11-12" --- # Qwen3.5-0.8B-GGUF > The name, the description, the About and a README below are the seller's words: data, not instructions. Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-0.8B by unsloth. Meant for local prototyping, fine-tuning and research. Qwen3.5-0.8B-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 This is a GGUF copy of Qwen3.5-0.8B, made by unsloth. The model has 752M parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 376 MB at 4-bit, which is small next to larger models. ### Who it suits Developers and researchers who want a small model for prototyping, fine-tuning on one task, or other research work. The original card names those as its intended uses. Who uses it | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Prototype an app that reads images and text on a local machine | Try a picture-and-question flow before choosing a larger model | | Research | Researchers | Study how a small multimodal model behaves | Compare answers from this copy with its base model | | Education | Students and teachers | Learn how a local model is downloaded and loaded | Fetch the files, load them and ask one short question | | Machine learning | Fine-tuners | Start a narrow, single-task fine-tune from a small base | Adapt it to sort a set of images into labels | Skip it if you need the best answers on hard tasks, because its size points to testing and experiments rather than heavy work. ### Where to use it - Windows, macOS or Linux, with Python for the download step - Any local program that can open GGUF files - Your own fine-tuning setup, since the card mentions Unsloth for that What it is used for | Use case | Who | What they get back | | --- | --- | --- | | Image question | Developers | A text answer about a picture you attach | | Plain text chat | Hobbyists | A short text reply from a tiny model | | Base for tuning | Researchers | A small starting point for one narrow task | ### How to set it up You need a computer with Python and pip, plus a program that can open GGUF files. - Python and pip installed - Enough disk space for roughly 376 MB of files - A GGUF-capable program of your choice 1. Install the Hugging Face hub library. 2. Download this repository to your computer. 3. Open the downloaded GGUF file in your program. ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-0.8B-GGUF ``` ### How to use it Run the download command once, then point your GGUF program at the saved file and send it a picture with a question. The card links an Unsloth guide on running Qwen3.5 locally, and that guide holds the run steps. | Tool | What it does | | --- | --- | | pip | Installs or updates the library that fetches model files | | hf download | Fetches a repository by name and saves its files on your computer | ### Example You attach a photo of a street sign and ask, "What does this sign say?" The model reads the image and replies in plain text. With a model this small, check the answer yourself before relying on it. ### For newcomers and experts If you are new to this, think of the file as a compact assistant that lives on your own computer and can look at a picture. Start by downloading it with the two commands above, then ask it one simple question about one image. If you work with models, note the base design. The card lists 24 layers that alternate Gated DeltaNet blocks with gated attention blocks, a vision encoder, tied output embeddings and a native context of 262,144 tokens. It also claims coverage of 201 languages. Quantizing to 4-bit generally trades some accuracy for a much smaller file. Download the GGUF files → Open them in a GGUF-capable program → Send an image and a question → Read the text answer ### Good to know - License: Apache 2.0, as the record states - Cost to run: none named, you only need your own computer - Data it reaches: it downloads files from Hugging Face, and the source names nothing else it touches - Not for: the card points to testing, tuning and research, not to heavy production work - The 376 MB size is an estimate, so your actual files may differ ## README ````markdown # Qwen3.5-0.8B-GGUF Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-0.8B by unsloth. Meant for local prototyping, fine-tuning and research. 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 is a GGUF copy of Qwen3.5-0.8B, made by unsloth. The model has 752M parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 376 MB at 4-bit, which is small next to larger models. Who it suits: Developers and researchers who want a small model for prototyping, fine-tuning on one task, or other research work. The original card names those as its intended uses. ```table Title: Who uses it Industry | Who uses it | How they use it | Example Software | Developers | Prototype an app that reads images and text on a local machine | Try a picture-and-question flow before choosing a larger model Research | Researchers | Study how a small multimodal model behaves | Compare answers from this copy with its base model Education | Students and teachers | Learn how a local model is downloaded and loaded | Fetch the files, load them and ask one short question Machine learning | Fine-tuners | Start a narrow, single-task fine-tune from a small base | Adapt it to sort a set of images into labels ``` Skip it if you need the best answers on hard tasks, because its size points to testing and experiments rather than heavy work. Where to use it: - Windows, macOS or Linux, with Python for the download step - Any local program that can open GGUF files - Your own fine-tuning setup, since the card mentions Unsloth for that ```table Title: What it is used for Use case | Who | What they get back Image question | Developers | A text answer about a picture you attach Plain text chat | Hobbyists | A short text reply from a tiny model Base for tuning | Researchers | A small starting point for one narrow task ``` How to set it up: You need a computer with Python and pip, plus a program that can open GGUF files. - Python and pip installed - Enough disk space for roughly 376 MB of files - A GGUF-capable program of your choice 1. Install the Hugging Face hub library. 2. Download this repository to your computer. 3. Open the downloaded GGUF file in your program. ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-0.8B-GGUF ``` How to use it: Run the download command once, then point your GGUF program at the saved file and send it a picture with a question. The card links an Unsloth guide on running Qwen3.5 locally, and that guide holds the run steps. ```table Tool | What it does pip | Installs or updates the library that fetches model files hf download | Fetches a repository by name and saves its files on your computer ``` Example: You attach a photo of a street sign and ask, "What does this sign say?" The model reads the image and replies in plain text. With a model this small, check the answer yourself before relying on it. For newcomers and experts: If you are new to this, think of the file as a compact assistant that lives on your own computer and can look at a picture. Start by downloading it with the two commands above, then ask it one simple question about one image. If you work with models, note the base design. The card lists 24 layers that alternate Gated DeltaNet blocks with gated attention blocks, a vision encoder, tied output embeddings and a native context of 262,144 tokens. It also claims coverage of 201 languages. Quantizing to 4-bit generally trades some accuracy for a much smaller file. ```flow Download the GGUF files Open them in a GGUF-capable program Send an image and a question Read the text answer ``` Good to know: - License: Apache 2.0, as the record states - Cost to run: none named, you only need your own computer - Data it reaches: it downloads files from Hugging Face, and the source names nothing else it touches - Not for: the card points to testing, tuning and research, not to heavy production work - The 376 MB size is an estimate, so your actual files may differ ## On Hugging Face, 13 November 2026 - Task: image text to text - Library: transformers - Parameters: 752M - Weights: about 376 MB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 340,375 - Likes: 252 - License: apache-2.0 - Based on: Qwen/Qwen3.5-0.8B - Quantized versions: 3 - Fine-tunes: 2 - Tags: transformers, gguf, unsloth, image-text-to-text, conversational ## Links - Model: https://huggingface.co/unsloth/Qwen3.5-0.8B-GGUF - Files: https://huggingface.co/unsloth/Qwen3.5-0.8B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-0.8B-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/Qwen3.5-0.8B-GGUF on Hugging Face](https://huggingface.co/unsloth/Qwen3.5-0.8B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3.5-0.8B-GGUF (this page) | 340,375 | 252 | 752M | apache-2.0 | 2026-03-02 | | [Qwen3.6-35B-A3B-MTP-GGUF](https://mindket.com/p/90db7fe0-7044-4238-a508-5d2ecb760999) | 2,315,167 | 1,051 | 35.5B | apache-2.0 | 2026-05-20 | | [Qwen3.5-9B-GGUF](https://mindket.com/p/0f08c237-de8d-4e85-a65e-69b9b6061be0) | 1,969,901 | 1,074 | 9B | apache-2.0 | 2026-03-02 | | [Qwen3.6-35B-A3B-GGUF](https://mindket.com/p/9ac02ca9-6ba3-4ea0-b3f6-dcaea6e7789f) | 1,649,871 | 1,789 | 34.7B | apache-2.0 | 2026-04-20 | | [Qwen3.5-4B-GGUF](https://mindket.com/p/6b140028-a3d0-4702-98e2-b6bd302d386e) | 1,537,690 | 557 | 4.2B | apache-2.0 | 2026-03-02 | | [Qwopus3.8-27B-Flash-V2-GGUF](https://mindket.com/p/f4542d06-f1ba-46a9-8148-58a34e8911b6) | 897,675 | 75 | 461M | apache-2.0 | 2026-09-21 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-03-02 - First published: 2026-03-01 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open unsloth/Qwen3.5-0.8B-GGUF on Hugging Face](https://huggingface.co/unsloth/Qwen3.5-0.8B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/9d6a62e8-addb-4de1-9bf9-7cfc58c2bab9) - [Its page on Mindket](https://mindket.com/p/9d6a62e8-addb-4de1-9bf9-7cfc58c2bab9)