Qwen-Image 2.1 uncensored: text encoder, finetune or GGUF, and what each one changes

"Qwen-Image 2.1 uncensored" gets searched as if it were one thing. It is at least three, and they change different parts of the pipeline. This post sorts them out, says which of them Locally Uncensored ships, and what the license still says no matter which one you pick.

Background, if you missed it: Alibaba Qwen published Qwen-Image 2.1 on 20 September 2026. One 7B set of weights does text to image and image editing. I wrote about running it locally when it came out. A few releases later, the uncensored side has filled in.

Two different meanings of uncensored

Where it runs. On your own machine nothing sits between your prompt and the model. No moderation layer reads the prompt or the picture. That part you get with the stock model already, as long as it runs locally.

What the weights do. The original model draws what it was trained to draw. The builds labelled uncensored change that, and they change it in different places:

Text encoder   the part that reads your prompt; can be processed to stop refusing
Image model    the part that draws; can be finetuned on other material
Both           community GGUF builds that change the weights

What the app ships

Locally Uncensored (open source, AGPL-3.0, 170,000+ downloads) has these in the Model Manager under Models, Image, Get new:

Qwen-Image 2.1 (Generate and Edit)   the original files, three of them, 16.1 GB
Qwen-Image 2.1 (No Filter)           same image model and VAE, a text encoder
                                     with its refusal direction removed (Heretic)
Noct Q (Qwen-Image 2.1, Unfiltered)  a community finetune; the image model
                                     itself is changed

The No Filter build only swaps the text encoder. If you already have Qwen-Image 2.1, only that encoder is downloaded, about 9 GB. With both encoders installed, the Expert settings in Create get a "Text encoder" row so you pick which one reads your prompt, for new pictures, for edits and for pictures made in chat. The official one stays the default.

Noct Q goes further: its notice says the transformer weights were modified. It uses the official text encoder and VAE, so on top of an existing install it is about 7 GB. The app treats it as Qwen-Image 2.1, so edits, the transparent background, the encoder choice and the prompt enhancer all work with it. I have not run Noct Q on my own hardware yet.

There is a matching pair for the prompt enhancer too, Official and No Filter. Both run on a 12 GB card and need ComfyUI 0.37.2 or newer.

Community files you add by hand

Outside the bundles there are GGUF builds on Hugging Face. As read off the repositories on 10 October 2026:

unsloth/Qwen-Image-2.1-GGUF                         original weights
  Q2_K 2.47 GB, Q4_K_M 4.2 GB, Q5_K_M 5.39 GB, F16 14.23 GB
abenzerps/Qwen-Image-2.1-Uncensored-GGUF            uncensored build
  Q4_K_M 4.6 GB, Q5_K_M 5.22 GB, Q6_K 5.88 GB, BF16 14.23 GB
pottokao/Qwen-Image-2.1-Text-Encoder-Heretic-GGUF   text encoder only
  Q4_K_M 5.03 GB, Q6_K 6.88 GB, Q8_0 8.71 GB

These go into ComfyUI by hand, and ComfyUI reads GGUF through a loader node you install first. I list them as their authors describe them. I have not tested them.

LoRAs exist now

When 2.1 came out there was no LoRA for it, and the older Qwen-Image speed LoRAs do not fit the new architecture. That changed within weeks: speed LoRAs for four to six steps (Viggle's turbo LoRAs, Alibaba PAI's acceleration LoRAs) and content LoRAs are on Hugging Face. On Windows and Linux they go into ComfyUI's models/loras folder and show up in the LoRA stack. I have not tested them with the bundle either.

Editing got better since launch

At launch the app's Edit lane took one reference image. Now, with Qwen-Image 2.1 on your own machine, small tiles under the source image take up to three more images. You name them in the prompt as image 2, image 3, for example "put the jacket from image 2 on the person". There is still no mask with this model. You describe the change in words.

There is also a "Transparent background" switch for new pictures. The result is saved as a PNG with an alpha channel.

On a Mac

The Mac build (Apple Silicon, beta) runs Qwen-Image 2.1 without ComfyUI, as quantized packs:

Qwen-Image 2.1 4-bit          needs 16 GB
Qwen-Image 2.1 8-bit, Turbo   need 24 GB

Qwen-Image 2.1 Turbo made an image in 38 seconds on an M5 Pro with 48 GB, the only Mac the build has run on. A LoRA that carries its own alpha is weighted alpha divided by rank there, the way ComfyUI does it.

The license does not change with the weights

Qwen-Image 2.1 is under the Qwen Research License. Research and evaluation are covered, commercial use needs a separate license from Alibaba Qwen. The community builds above name the same license. An uncensored text encoder does not turn a research license into a commercial one. If you need Apache 2.0 terms, Qwen-Image 2512 and Qwen-Image-Edit 2511 are still under Apache 2.0.

Short version

Running Qwen-Image 2.1 locally already removes any moderation layer. The No Filter build swaps only the text encoder (about 9 GB on top), Noct Q changes the image model itself (about 7 GB on top), and community GGUF builds go in by hand. Edits take up to three extra images and no mask, the Mac runs it from 16 GB, and every variant is still research and evaluation only.

The code is at github.com/PurpleDoubleD/locally-uncensored, and the longer page with the files and the FAQ is Qwen-Image 2.1, uncensored on your own card.