Mindket

Qwen3.5-2B-GGUF

Newversion 1 · updated

Overview

Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-2B by unsloth. Meant for local prototyping, fine-tuning and research.

Qwen3.5-2B-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Python and pip installed
  • Enough disk space for roughly 941 MB of files
  • A GGUF-capable program of your choice
Runs in
  • 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
Start with
pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-GGUF

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

This is a GGUF copy of Qwen3.5-2B, made by unsloth. The model has 1.9B parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 941 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
IndustryWho uses itHow they use itExample
SoftwareDevelopersPrototype an app that reads images and text on a local machineTry a picture-and-question flow before choosing a larger model
ResearchResearchersStudy how a small multimodal model behavesCompare answers from this copy with its base model
EducationStudents and teachersLearn how a local model is downloaded and loadedFetch the files, load them and ask one short question
Machine learningFine-tunersStart a narrow, single-task fine-tune from a small baseAdapt 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 caseWhoWhat they get back
Image questionDevelopersA text answer about a picture you attach
Plain text chatHobbyistsA short text reply from a small model
Base for tuningResearchersA 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 941 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.
pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-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.

ToolWhat it does
pipInstalls or updates the library that fetches model files
hf downloadFetches 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.

  1. Download the GGUF files
  2. Open them in a GGUF-capable program
  3. Send an image and a question
  4. 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 941 MB size is an estimate, so your actual files may differ

README and files

README

Qwen3.5-2B-GGUF

Reads images and text and answers in text, as a small GGUF copy of Qwen3.5-2B 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 Qwen3.5-2B, made by unsloth. The model has 1.9B parameters and takes an image plus text, then answers in text. Hugging Face estimates the files at about 941 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.

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
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 small 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 941 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.
pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-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 941 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: 1.9B
  • Weights: about 941 MB at 4-bit (estimate)
  • Formats: GGUF
  • Downloads in the last 30 days: 505,712
  • Likes: 176
  • License: apache-2.0
  • Based on: Qwen/Qwen3.5-2B
  • Quantized versions: 2
  • Fine-tunes: 2
  • Tags: transformers, gguf, unsloth, image-text-to-text, conversational

Links

Get the model

Download its files with Hugging Face's command line:

pip install -U huggingface_hub
hf download unsloth/Qwen3.5-2B-GGUF

Then follow the usage in its model card. Nothing in this kit runs by itself.

Files
README.md  5 KB

1 file, 5 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-13

Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

ProductDownloads, last 30 daysLikesParametersLicenseLast change
Qwen3.5-2B-GGUF This page505,7121761.9Bapache-2.0
Qwen3.6-35B-A3B-MTP-GGUFShares unsloth · image-text-to-text · gguf2,315,1671,05135.5Bapache-2.0
Qwen3.5-9B-GGUFShares unsloth · image-text-to-text · gguf1,969,9011,0749Bapache-2.0
Qwen3.6-35B-A3B-GGUFShares unsloth · image-text-to-text · gguf1,649,8711,78934.7Bapache-2.0
Qwen3.5-4B-GGUFShares unsloth · image-text-to-text · gguf1,537,6905574.2Bapache-2.0
Qwopus3.8-27B-Flash-V2-GGUFShares unsloth · image-text-to-text · gguf897,67575461Mapache-2.0
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

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