Qwen Image 2.1 - Free Local AI Images
💙⚡Become a member – https://tinyurl.com/blmemberEvery picture in the first few seconds of this video came out of one free image model running on a laptop. I installed Qwen Image 2.1 on an M3 Max MacBook Pro, timed it, and then gave it exactly the same prompts as four paid models, so you can decide whether you still need to pay for every picture.
I cover installing it on a Mac and on a PC, what the 8-bit and full versions cost you in memory and time, and real transparent cutouts. Then come six rounds against GPT Image 2.5, Seedream 5.0 Pro, Nano Banana 2 and FLUX.2 [max]: a lettered poster, a product label, a real person, a hotel lobby, a food truck and a sticker. After that it faces the other open models, Ideogram 4.0 and Cosmos 3 Super, and I run five extra text tests against GPT Image 2.5.
Qwen surprised me on skin. Its faces look like real people, and it's the only free model that gave me a true see-through cutout. Where it struggles is lettering it has to invent. Give it the exact words and it mostly spells them right, but a weekday list or a sales table it makes up comes out as gibberish. GPT Image 2.5 came first overall at about four cents a picture. Qwen came last on the comparison, but it cost nothing and never refused a prompt. On the M3 Max it took about eight and a half minutes a picture with the 8-bit version, and the full model was actually faster if you have the memory for it.
If you make lots of concept art, mood boards or product drafts and don't want a bill for every try, this is worth the wait on a Mac with 32 GB or more. If you need one polished picture with words on it right now, a few cents online is still the easier call.
HOW TO INSTALL IT
On a Mac (what I used: an M3 Max MacBook Pro with 64 GB)
You need Apple silicon, 32 GB of memory or more, Python 3.10 or newer, and about 33 GB of free disk space. Open Terminal and run these three lines:
python3 -m venv qwen && source qwen/bin/activate
pip install mflux
mflux-generate-qwen-2.1 --prompt "your prompt here" -q 8 --steps 40 --seed 7 --width 1536 --height 864 --output first.png
The first run downloads the model once (about 33 GB). The -q 8 setting is the lighter 8-bit version, which peaked at about 30 GB of memory on the M3 Max. Leave it off to run the full model, which needs about 46 GB.
On a PC (Windows 10+, NVIDIA graphics card)
I didn't test on a PC, so these figures come from published tests. Plan on a card with 24 GB of video memory; smaller cards need a compressed version of the model. The easiest route is the free ComfyUI desktop app:
1. Install ComfyUI Desktop from comfy.org/download
2. Open Templates and search for Qwen-Image-2.1
3. Let it download the three model files it asks for (about 17 GB)
4. Type your prompt and press Run
If you'd rather use the official code, install Python 3.12 and Git for Windows, then in PowerShell:
py -3.12 -m venv qwen
qwen\Scripts\Activate.ps1
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu130
pip install git+https://github.com/huggingface/diffusers transformers accelerate pillow
python run.py
run.py loads the model with QwenImage21Pipeline and enable_model_cpu_offload(), as in the example on the model's Hugging Face page.
CHAPTERS
00:00 Made on a laptop for $0
00:15 What Qwen Image 2.1 is
00:48 Install it on a Mac or PC
01:55 The first picture and the wait
02:12 Fewer passes against 40 passes
02:58 Real transparent cutouts
03:54 The test: four paid models, same prompt
04:14 Round 1: a lettered poster
04:50 Round 2: a product label
05:23 Round 3: a real person
06:15 Round 4: a hotel lobby
06:46 Round 5: a food truck
07:28 Round 6: a sticker cutout
08:05 Realism: five portraits
09:19 Against Ideogram 4.0 and Cosmos 3 Super
10:23 Five text tests against GPT Image 2.5
10:53 Fewer filters
11:47 Full model, 8-bit and reference faces
12:55 How big it can go
13:28 My ranking
14:06 Which one to use
Try it on your own machine and tell me in the comments what you made with it. Receive SMS online on sms24.me
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