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Qwen-Image-2.1-W4A4-int4

Text-to-Image
Diffusers
Safetensors
image-to-image
quantization
w4a4
svdquant
gptq
nunchaku
8-bit precision
Model card Files
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 Community
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adhikjoshi commited on
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W4A4 int4 checkpoint, SVDQuant + GPTQ, LPIPS 0.1836

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Files changed (13) hide show
  1. .gitattributes +6 -0
  2. NOTICE +1 -0
  3. README.md +90 -0
  4. config.json +20 -0
  5. diffusion_pytorch_model.safetensors +3 -0
  6. nunchaku_w4a4.json +1673 -0
  7. samples/flat.png +3 -0
  8. samples/landscape.png +3 -0
  9. samples/orrery.png +3 -0
  10. samples/portrait.png +3 -0
  11. samples/text-board.png +3 -0
  12. samples/text-sign.png +3 -0
  13. w4a4_build.json +161 -0
.gitattributes CHANGED
@@ -33,3 +33,9 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ samples/flat.png filter=lfs diff=lfs merge=lfs -text
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+ samples/landscape.png filter=lfs diff=lfs merge=lfs -text
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+ samples/orrery.png filter=lfs diff=lfs merge=lfs -text
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+ samples/portrait.png filter=lfs diff=lfs merge=lfs -text
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+ samples/text-board.png filter=lfs diff=lfs merge=lfs -text
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+ samples/text-sign.png filter=lfs diff=lfs merge=lfs -text
NOTICE ADDED
@@ -0,0 +1 @@
 
 
1
+ Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved.
README.md ADDED
@@ -0,0 +1,90 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
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+ license: other
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+ license_name: qwen-research
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+ license_link: https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE
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+ base_model: Qwen/Qwen-Image-2.1
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+ tags: [text-to-image, image-to-image, quantization, w4a4, svdquant, gptq, nunchaku]
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+ pipeline_tag: text-to-image
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+ ---
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+
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+ # Qwen-Image-2.1 W4A4 (int4)
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+
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+ Built with Qwen.
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+
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+ > **Non-commercial use only.** An educational artifact under the Qwen Research License,
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+ > which the base model carries. Commercial use needs a separate licence from the rights
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+ > holder; publishing this here does not grant one.
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+
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+ 4-bit weights, 4-bit activations, for the Qwen-Image-2.1 transformer. Calibrated with
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+ SVDQuant, error-compensated with GPTQ, packed for Nunchaku's fused kernel.
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+ **4.34 GB** against about 10 GB for the same layers in bf16.
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+
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+ The low-rank branch is fused into the 4-bit GEMM, which is where the speed comes from —
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+ an unfused branch gives back 24–34% of it.
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+
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+ ## Hardware
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+
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+ **sm_75 through sm_120** — Ada (4090, L40S) and Blackwell alike.
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+
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+ ## Measured
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+
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+ | card | cap | seconds | vs bf16 | resident GB | LPIPS vs bf16 |
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+ |---|---|---|---|---|---|
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+ | RTX 4090 48GB | sm_89 | 11.576 | 1.84x | 21.35 | 0.231 |
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+ | RTX PRO 6000 Max-Q | sm_120 | 37.616 | 0.35x | 21.29 | 0.1836 |
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+
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+ 40 steps, 1024×1024, seed 42, six prompts. LPIPS is AlexNet against the bf16 image of
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+ the same prompt on the same card.
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+
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+ **GPTQ is worth 6% here**:
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+ 0.1946 with round-to-nearest against **0.1836** with GPTQ, at the same
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+ speed, the same file size and the same resident memory — it only changes which grid point
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+ each weight lands on.
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+
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+ Read LPIPS as distance from the bf16 trajectory, not as damage. On a dense-text prompt
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+ every build renders the text correctly while scoring 0.24–0.35, and on one prompt the
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+ bf16 reference garbles a sign that this checkpoint renders correctly — and is scored
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+ worse for it.
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+
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+ Only the transformer is quantized. The Qwen3-VL text encoder stays bf16 and is about
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+ 16.3 GB of a 21.5 GB resident total, so it, not this file, decides how many reference
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+ images fit on a card.
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+
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+ ## Requirements
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+
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+ Packed for a specific kernel. The layout is an MMA fragment swizzle, so a different
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+ Nunchaku build may read it incorrectly — and would produce a wrong image rather than an
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+ error. The loader checks and warns.
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+
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+ ```
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+ torch==2.12.1
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+ nunchaku==1.3.0.dev20260306+cu13.0torch2.12
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+ ```
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+
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+ ## Loading
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+
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+ ```python
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+ import torch
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+ from diffusers import QwenImage21Pipeline
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+ from quantize import nunchaku_io
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+
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+ transformer = nunchaku_io.load_checkpoint(precision="int4", device="cuda")
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+ pipe = QwenImage21Pipeline.from_pretrained(
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+ "Qwen/Qwen-Image-2.1", torch_dtype=torch.bfloat16, transformer=transformer)
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+ ```
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+
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+ `nunchaku_io` and the build pipeline: https://github.com/ModelsLab/qwen-image-2-1-server
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+
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+ ## How it was built
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+
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+ Smoothing factors from real activation statistics (SmoothQuant, α=0.5), a rank-128 SVD
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+ branch kept in bf16, and the residual rounded onto Nunchaku's grid by GPTQ against a
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+ calibration Hessian. One Hessian pass, 128 distinct inputs across 224 layers, 24 GB
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+ resident, ~5 minutes.
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+
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+ `w4a4_build.json` records the whole build, including per-layer GPTQ statistics.
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+
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+ ## License
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+
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+ Derivative of [Qwen/Qwen-Image-2.1](https://huggingface.co/Qwen/Qwen-Image-2.1) under the
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+ **Qwen Research License Agreement** — non-commercial only. See `NOTICE`.
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