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wavespeed/
Qwen-Image-Edit-l8v1.1-e4m3

Name: Qwen-Image-Edit-l8v1.1-e4m3
Availability: InStock

diffusers

QwenImageEditPipeline

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Qwen-Image-Edit-l8v1.1-e4m3

Qwen-Image-Edit with the Qwen-Image-Lightning 8-step V1.1 LoRA fused into the transformer, then quantized to FP8 (e4m3). Saved as a complete QwenImageEditPipeline.

l8v1.1 in the repo name is Lightning, 8 steps, V1.1.

What was changed

Qwen-Image-Lightning-8steps-V1.1.safetensors is loaded as a LoRA, fused into the base transformer, and unloaded — so the published weights carry the step distillation directly and no LoRA is needed at inference.
All 60 transformer blocks are then quantized to e4m3_e4m3_dynamic (float8_e4m3fn weights, dynamically scaled float8_e4m3fn activations).

The Qwen2.5-VL text encoder, the processor and the VAE are untouched and stay in bf16. Weights are pickled .bin shards, so loading requires use_safetensors=False.

Usage

Run it at roughly 8 steps with CFG off — that is what the fused LoRA was distilled for. Running it at 40 steps like the undistilled model wastes compute and does not improve the result.

python

import torch
from diffusers import QwenImageEditPipeline
from diffusers.utils import load_image

pipe = QwenImageEditPipeline.from_pretrained(
    "wavespeed/Qwen-Image-Edit-l8v1.1-e4m3",
    torch_dtype=torch.bfloat16,
    use_safetensors=False,
).to("cuda")

out = pipe(
    image=load_image("input.png"),
    prompt="replace the sky with a clear night sky",
    num_inference_steps=8,
    true_cfg_scale=1.0,
).images[0]

License

Apache-2.0. Both Qwen-Image-Edit and Qwen-Image-Lightning are Apache-2.0.