--- title: "Qwen3.5-4B-GGUF" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6b140028-a3d0-4702-98e2-b6bd302d386e" updated: "2026-11-12" --- # Qwen3.5-4B-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 Qwen3.5-4B, a small model that reads images and text and answers in text, for people running models locally. Qwen3.5-4B-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 Qwen3.5-4B-GGUF is a GGUF copy of Qwen3.5-4B, made by Unsloth. The base model reads images and text and replies in text. The record lists 4.2B parameters, and the 4-bit weights come to about 2.1 GB by its estimate. The Qwen3.5 family is a causal language model with a vision encoder. It lists support for 201 languages and dialects, and a context length of 262,144 tokens natively. ### Who it suits It suits people who want a small multimodal model on their own computer, without sending their files to a hosted service. A file of about 2.1 GB fits on many ordinary machines. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Run a local model for text and image questions | Asking what a screenshot shows | | Education | Students | Practice with a model that works offline | Explaining a diagram in a textbook | | Office work | Analysts | Summarize documents and read charts locally | Describing a chart image in words | | Research | Hobbyist researchers | Try a recent small model on their own hardware | Comparing answers across languages | Skip it if you want a hosted chat service and do not run models yourself. ### Where to use it - Local apps and libraries that load GGUF files - Windows, macOS or Linux, with Python for the download step - Your own computer, with no hosted service needed | Use case | Who | What they get back | | --- | --- | --- | | Ask about an image | Anyone with a local setup | A written answer about the picture | | Long document questions | Researchers | Answers from a context window of 262,144 tokens | | Multilingual chat | Global teams | Replies in many of the 201 languages the card lists | ### 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 2.1 GB of free disk space for the 4-bit weights 1. Install the Hugging Face hub package with pip. 2. Download the repository with the hf command. 3. Open the GGUF file in your local app. The model card has the run details. ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-4B-GGUF ``` ### How to use it Once the file is loaded in your local app, you chat with it or send it images with a question. Training your own variant on your machine is also possible through Unsloth, the maker of this copy. ### Example You load the file and attach a photo of a chart with the question "What does this chart show?" The model answers in text. It describes what the picture contains and what the question needs. ### For newcomers and experts Start small. Download the file, open it in a GGUF-capable app and ask one plain question before you try images. If it runs well, add a picture. Qwen3.5 mixes Gated DeltaNet layers with gated attention layers, in a pattern repeated 8 times across 32 layers. The card calls this a hybrid design that keeps inference fast. The GGUF copy trades some precision for a much smaller file. Unsloth says its Dynamic 2.0 quant method keeps accuracy high, and the card gives a native context of 262,144 tokens that can stretch to 1,010,000. Download the GGUF file with hf → Load it in a local app → Send text or an image → The model replies in text ### Good to know - License: Apache 2.0 - Cost to run: none named, but you need a machine with room for about 2.1 GB of weights - Data it reaches: it downloads files from Hugging Face onto your computer ## README ````markdown # Qwen3.5-4B-GGUF Unsloth's GGUF quantized copy of Qwen3.5-4B, a small model that reads images and text and answers in text, for people running models 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: Qwen3.5-4B-GGUF is a GGUF copy of Qwen3.5-4B, made by Unsloth. The base model reads images and text and replies in text. The record lists 4.2B parameters, and the 4-bit weights come to about 2.1 GB by its estimate. The Qwen3.5 family is a causal language model with a vision encoder. It lists support for 201 languages and dialects, and a context length of 262,144 tokens natively. Who it suits: It suits people who want a small multimodal model on their own computer, without sending their files to a hosted service. A file of about 2.1 GB fits on many ordinary machines. ```table Industry | Who uses it | How they use it | Example Software | Developers | Run a local model for text and image questions | Asking what a screenshot shows Education | Students | Practice with a model that works offline | Explaining a diagram in a textbook Office work | Analysts | Summarize documents and read charts locally | Describing a chart image in words Research | Hobbyist researchers | Try a recent small model on their own hardware | Comparing answers across languages ``` Skip it if you want a hosted chat service and do not run models yourself. Where to use it: - Local apps and libraries that load GGUF files - Windows, macOS or Linux, with Python for the download step - Your own computer, with no hosted service needed ```table Use case | Who | What they get back Ask about an image | Anyone with a local setup | A written answer about the picture Long document questions | Researchers | Answers from a context window of 262,144 tokens Multilingual chat | Global teams | Replies in many of the 201 languages the card lists ``` 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 2.1 GB of free disk space for the 4-bit weights 1. Install the Hugging Face hub package with pip. 2. Download the repository with the hf command. 3. Open the GGUF file in your local app. The model card has the run details. ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-4B-GGUF ``` How to use it: Once the file is loaded in your local app, you chat with it or send it images with a question. Training your own variant on your machine is also possible through Unsloth, the maker of this copy. Example: You load the file and attach a photo of a chart with the question "What does this chart show?" The model answers in text. It describes what the picture contains and what the question needs. For newcomers and experts: Start small. Download the file, open it in a GGUF-capable app and ask one plain question before you try images. If it runs well, add a picture. Qwen3.5 mixes Gated DeltaNet layers with gated attention layers, in a pattern repeated 8 times across 32 layers. The card calls this a hybrid design that keeps inference fast. The GGUF copy trades some precision for a much smaller file. Unsloth says its Dynamic 2.0 quant method keeps accuracy high, and the card gives a native context of 262,144 tokens that can stretch to 1,010,000. ```flow Download the GGUF file with hf Load it in a local app Send text or an image The model replies in text ``` Good to know: - License: Apache 2.0 - Cost to run: none named, but you need a machine with room for about 2.1 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 - Library: transformers - Parameters: 4.2B - Weights: about 2.1 GB at 4-bit (estimate) - Formats: GGUF - Downloads in the last 30 days: 1,537,690 - Likes: 557 - License: apache-2.0 - Based on: Qwen/Qwen3.5-4B - Quantized versions: 10 - Fine-tunes: 2 - Tags: transformers, gguf, unsloth, image-text-to-text, conversational ## Links - Model: https://huggingface.co/unsloth/Qwen3.5-4B-GGUF - Files: https://huggingface.co/unsloth/Qwen3.5-4B-GGUF/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download unsloth/Qwen3.5-4B-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/Qwen3.5-4B-GGUF on Hugging Face](https://huggingface.co/unsloth/Qwen3.5-4B-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 | | --- | --- | --- | --- | --- | --- | | Qwen3.5-4B-GGUF (this page) | 1,537,690 | 557 | 4.2B | 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 | | [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 | | [Muse Glimmer 30B GGUF](https://mindket.com/p/31b81c35-03e2-4c43-ad62-fe42f4b51f11) | 692,334 | 592 | 27.9B | apache-2.0 | 2026-08-10 | 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: 2026-03-02 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open unsloth/Qwen3.5-4B-GGUF on Hugging Face](https://huggingface.co/unsloth/Qwen3.5-4B-GGUF) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6b140028-a3d0-4702-98e2-b6bd302d386e) - [Its page on Mindket](https://mindket.com/p/6b140028-a3d0-4702-98e2-b6bd302d386e)