Qwen-Image-2.1 Guide: Model Files
About This Model
Qwen-Image-2.1 is an image generation model from Alibaba’s Qwen team. Its distinguishing feature is that text-to-image generation and image editing live in one model, and its image-generation component is compact for this class of model, at 7B parameters (32 DiT layers). It outputs images of about 4 megapixels, such as 2048×2048 at 1:1.
The publisher highlights four improvements:
- Native support for transparent (RGBA) images. The same model can generate images with transparent backgrounds from text, edit transparent layers, and cut subjects out of photos. For logos, icons and compositing assets, no separate background-removal step is needed.
- Up to 10 reference images. You can place a person or product in a new scene while preserving their appearance. Areas to edit can be marked with circles, painted annotations, or a separate mask.
- Better typography, portrait lighting and fine texture, according to the publisher.
- A lightweight design (mixed-granularity attention and prefix KV cache reuse) keeps compute costs down.
About the “PE" companion models: Two helper models that rewrite short requests into detailed image prompts were released alongside it. PE-T2I (for text-to-image) turns a brief request in any language into a detailed English prompt plus a recommended aspect ratio; PE-I2I (for image editing) takes a vague editing instruction and the input image(s) and produces a precise, actionable instruction. Both are fine-tuned from Qwen3.5-VL 9B. This site’s article on the official models and the “Distributed Files" table below cover PE-I2I, not the image generator itself.
What Makes It Stand Out
The model card does not include a numeric comparison with other models, so this page does not discuss benchmark numbers and focuses on capabilities instead.
- Generation, editing and transparency handled by one model is the headline. Work that used to require a generation model, an editing model and a background-removal tool can run in a single pipeline.
- The small 7B generation component helps when running on local GPUs, though total memory use—including the text-understanding part—depends on the format you use.
Running It Locally
- The official route is diffusers’
QwenImage21Pipeline(at the time of writing, you need to install diffusers from GitHub). - Community GGUF builds are also available. Articles on this site include an “Uncensored" build from a third party with the safety tuning removed; its weights differ from the official model, so it is a separate model.
- The license is the Qwen Research License, which limits use to research and evaluation. Commercial use requires a separate license from the publisher, and redistributions must include the required attribution notice.
Sources: model cards and license for Qwen/Qwen-Image-2.1, Qwen/Qwen-Image-2.1-PE-T2I and Qwen/Qwen-Image-2.1-PE-I2I, as of 2026-09-25.
Our Coverage and Data
Everything Local Model Watch has published about the Qwen-Image-2.1 family: 3 article(s) covering the base model and its fine-tunes, plus converted builds we tracked after publication. Memory requirements below are computed by this site from file sizes, not quoted from model cards. Part of our model family index.
At a Glance
| Item | Value |
|---|---|
| Base model(s) | Qwen/Qwen-Image-2.1, Qwen/Qwen-Image-2.1-PE-T2I |
| Publisher | Alibaba (Qwen) |
| License (model card) | other |
| Articles | 3 |
Can You Run It Locally?
The publisher distributes this model as safetensors.
License — other: A custom license from the publisher. Check the original terms directly, including whether commercial use is permitted.
Compiled by this site’s code from the published formats and the license field. License summaries are not legal advice — check the publisher’s original terms before relying on them.
This assessment is for Qwen/Qwen-Image-2.1-PE-I2I.
Distributed Files
Weight files published in Qwen/Qwen-Image-2.1-PE-I2I, listed by this site from the Hugging Face API. Sizes are the actual file sizes.
| File | Size |
|---|---|
model-00001.safetensors |
5.07GB |
model-00002.safetensors |
5.09GB |
model-00003.safetensors |
5.09GB |
model-00004.safetensors |
3.57GB |
Quantized and Converted Variants
→ Scroll horizontally to see all columns
| Added | Publisher | Format | Repository | Smallest VRAM tier (build, est. memory) |
|---|---|---|---|---|
| 2026-09-23 | unsloth | GGUF | unsloth/Qwen-Image-2.1-GGUF | Q3_K_XL 4.0GB (fits in 4GB VRAM) |
| 2026-09-23 | unsloth | FP8 | unsloth/Qwen-Image-2.1-FP8 | FP8 8.0GB (fits in 8GB VRAM) |
File sizes of each build:
- Available builds in unsloth/Qwen-Image-2.1-GGUF: Q2_K 2.3GB / Q3_K_S 2.5GB / Q3_K_M 3.0GB / Q3_K_XL 3.4GB / Q4_K_S 3.6GB / Q4_K_M 3.9GB / Q5_K_S 4.2GB / Q5_K_M 5.0GB / Q6_K 5.8GB / Q6_K_XL 6.3GB / Q8_0 7.1GB / F16 13.3GB
- Available builds in unsloth/Qwen-Image-2.1-FP8: FP8 6.6GB / INT8 6.8GB / FP8(Qwen-Image-2.1-text_encoder-FP8) 8.7GB
This section is appended automatically by Local Model Watch when a converted build of this model appears after publication. Memory figures are estimated from the size of the distributed files.
Articles (the family’s own models first, then newest)
| Published | Model | Type | Article |
|---|---|---|---|
| 2026-09-20 | Qwen/Qwen-Image-2.1-PE-I2I | Image, Video and Audio | Qwen-Image-2.1 Released: Open-Weight Image Gen & Editing |
| 2026-09-23 | Viggle/Qwen-Image-2.1-viggle-turbo | Image, Video and Audio | Qwen-Image-2.1-viggle-turbo Image Generation Model: 48GB+ VRAM |
| 2026-09-21 | abenzerps/Qwen-Image-2.1-Uncensored-GGUF | Image, Video and Audio | Qwen-Image-2.1-Uncensored-GGUF Image Generation Model: 16GB+ VRAM |
Repositories
- Qwen/Qwen-Image-2.1
- Qwen/Qwen-Image-2.1-PE-T2I
- Viggle/Qwen-Image-2.1-viggle-turbo
- abenzerps/Qwen-Image-2.1-Uncensored-GGUF
- Qwen/Qwen-Image-2.1-PE-I2I
Last updated 2026-09-28 (JST). The explanation at the top of this page was written with the help of AI from the primary sources it cites. The tables and lists under “Our Coverage and Data" are assembled by code from our article log.