Qwen3.5-2B

Qwen3.5-2B

A small 2B Qwen model that reads text and images and replies in text, for developers who prototype, fine-tune or run research with the transformers library.

Made by Qwen 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: Qwen3.5-2B is a small post-trained model from Qwen with about 2.3B parameters by Hugging Face's count. It reads text and images and replies in text. It is built from Qwen3.5-2B-Base and comes as Safetensors files for the transformers library. The card also names vLLM, SGLang and KTransformers as compatible. The card points it at quick prototypes, tuning for a single task and general research.

Who it suits: It suits developers, researchers and machine learning engineers who want a small multimodal model to test ideas on or to adapt to a task of their own.

Title: Who uses this model
Industry | Who uses it | How they use it | Example
Software | Developers | Prototype features that read pictures and text | Try a small model before moving to a larger one
AI research | Researchers | Study a compact multimodal model | Compare it with the other Qwen3.5 sizes
Machine learning | Fine-tuners | Start a custom model from a small checkpoint | Train it further on a task of their own

If you need the best accuracy on hard tasks, you can skip it, since the card points it at prototyping and research.

Where to use it:

• Python scripts that use the transformers library
• Servers such as vLLM, SGLang or KTransformers, which the card says work with it
• Windows, macOS or Linux with Python, for downloading the files

Title: Jobs it does
Use case | Who | What they get back
Picture and text questions | Developers | A written answer about an image you supply
Prototyping | Product teams | A quick test of an idea on a small model
Fine-tuning | Machine learning engineers | A starting point for a model built for one task
Multilingual text | Global teams | Coverage of 201 languages and dialects, per the card

How to set it up: You need Python and the huggingface_hub package. The weights are about 4.5 GB in BF16, or about 1.1 GB at 4-bit by Hugging Face's estimate, so plan your disk and memory around that.

• Python with pip
• About 4.5 GB of free disk space for the BF16 files
• The transformers library, or one of the servers named above

1. Install huggingface_hub.
2. Download the model files with the hf command.
3. Load them with your chosen library, following the full model card.

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

How to use it: The part of the card visible here shows no run steps, so check the full card for the exact loading code. The general pattern for an image text to text model is to load it, pass a picture with a question and read the text reply.

Title: Main commands
Tool | What it does
pip install -U huggingface_hub | Installs the helper that downloads model files
hf download Qwen/Qwen3.5-2B | Saves the model files on your computer

Example: You download the files, load the model, give it a photo and ask what is in it. A typical reply is a short written description of the picture.

For newcomers and experts: A small model like this is cheap to try. A first small test is to download it and ask one question about a picture you own.

The language model has 24 layers and a hidden size of 2048. Its layout repeats six times, with three gated delta layers followed by one gated attention layer, and a vision encoder sits in front. It handles 262,144 tokens of context natively.

Picture and text prompt
Vision encoder reads the image
Hybrid language model layers
Text reply

Good to know: In the card's non-thinking MMLU-Pro row, this model scores 55.3, against 69.6 for Qwen3-4B-2507 and 29.7 for Qwen3.5-0.8B. Other people have published 318 quantized and 684 fine-tuned versions.

Title: Estimated weight size
BF16: 4.5 GB
4-bit: 1.1 GB

• 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: relying on it for hard tasks without checking, since the card describes it as a prototyping and research model.

On Hugging Face, 13 November 2026

• Task: image text to text
• Library: transformers
• Parameters: 2.3B
• Weights: about 4.5 GB in BF16; about 1.1 GB at 4-bit (estimate)
• Formats: Safetensors
• Downloads in the last 30 days: 4,044,746
• Likes: 479
• License: apache-2.0
• Based on: Qwen/Qwen3.5-2B-Base
• Quantized versions: 323
• Fine-tunes: 698
• Tags: transformers, safetensors, qwen3_5, image-text-to-text, conversational

Links

• Model: https://huggingface.co/Qwen/Qwen3.5-2B
• Files: https://huggingface.co/Qwen/Qwen3.5-2B/tree/main

Get the model

Download its files with Hugging Face's command line:

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

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