Qwen-Edit-2511 - quantized - int4 - compact
Install
quant-qwen-edit quantizes Qwen-Image-Edit and verifies the result empirically. Precision is assigned per layer from activation-aware sensitivity, not uniformly; The int4-compact recipe runs 1024×1024 in 19.5 GB with no offloading, at 0/14 cases outside natural sampler variance. Loads into any diffusers pipeline with one call.
You will need to install it using:
pip install https://huggingface.co/404-Gen/Qwen-Edit-2511-int4-compact/resolve/main/quant_qwen_edit-0.6.1-py3-none-any.whl
Use
import torch
from PIL import Image
from quant_qwen_edit import load_quantized_pipeline
pipe = load_quantized_pipeline(
"404-Gen/Qwen-Edit-2511-int4-compact", # HF repo id, or a local directory
torch_dtype=torch.bfloat16,
device="cuda", # no offloading needed
)
image = Image.open("photo.jpg").convert("RGB").resize((1024, 1024), Image.LANCZOS)
out = pipe(
prompt="Place a clean printed label on the apple that reads ORGANIC.",
negative_prompt=" ",
image=image,
height=1024,
width=1024,
num_inference_steps=40,
true_cfg_scale=4.0,
generator=torch.Generator("cuda").manual_seed(7),
).images[0]
out.save("edited.png")
In case custom scheduler is needed to supply or enabling compilation:
pipe = load_quantized_pipeline(
"404-Gen/Qwen-Edit-2511-int4-compact",
scheduler=my_scheduler, # any component -> forwarded to from_pretrained
revision="222829069d", # pin the quantized repo to a commit
token=hf_token, # if the repo is private
offload="model", # evict the text encoder; ~13.5 GB instead of ~23
compile=True, # ~2x faster after a one-off kernel build
)
The pipeline is a stock QwenImageEditPlusPipeline — schedulers, callbacks,
LoRA and enable_model_cpu_offload() all work normally.
Faster (optional)
pipe = load_quantized_pipeline(..., compile=True)
24.1 s / 20 steps instead of 40.3 s — faster than bf16. Costs a one-off kernel build on the first call, and recompiles if you change resolution.
Measured
RTX PRO 6000 Blackwell, 1024x1024, no offloading.
| peak VRAM | 19.54 GB |
| latency | 40.3 s / 20 steps · 80.6 s / 40 steps |
| on disk | 18 GB (transformer 12, text encoder 5.7, VAE 0.24) |
| transformer | 40.85 GB -> 11.91 GB (0.29x) |
| text encoder | 16.58 GB -> 5.7 GB |
Quality
Measured against the sampler's own seed-to-seed variance: render bf16 twice at different seeds, see how far two equally-valid samples sit apart, then ask whether quantizing moves the output further than re-rolling the seed does. At or below 1.0 it does not.
| mean | worst | cases over 1.0 | |
|---|---|---|---|
| int4-compact | 0.51x | 0.72x | 0 of 14 |
| ovedrive NF4 (same harness) | 0.58x | 1.03x | 2 of 14 |
14 cases spanning text rendering, identity preservation, fine detail, global relighting and structural edits.
Licenses
Base model is Qwen/Qwen-Image-Edit-2511, Apache-2.0