Qwen-Image-Edit-2511-NVFP4

ANXS1/Qwen-Image-Edit-2511-NVFP4

Qwen-Image-Edit-2511-NVFP4 is a machine learning model from ANXS1. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for diffusion-single-file. The card lists the license as apache-2.0.

I did rough calibration, but the quality seems okay.

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At a glance

Library: diffusion-single-file
License: apache-2.0
Access: Public
Created: Jun 16, 2026
Updated: Jun 16, 2026
SHA: b1a7de48

Base models

Model card

From the Hugging Face model README

NVFP4 Qunatization model of Qwen-Image-Edit-2511 for ComfyUI

I did rough calibration, but the quality seems okay.

Generation speed

Tested on RTX5090(400W), ComfyUI with torch2.9.1+cu130
Generates 832x1280, 4steps, cfg1.0
Second run measured by varying only the seed

#nvfp4
100%|███████████████████| 4/4 [00:01<00:00,  2.52it/s]
Prompt executed in 3.45 seconds
#fp8mixed
100%|███████████████████| 4/4 [00:04<00:00,  1.02s/it]
Prompt executed in 6.09 seconds
#bf16
100%|███████████████████| 4/4 [00:06<00:00,  1.62s/it]
Prompt executed in 9.80 seconds

Quantized modules

{
  "block_name": "transformer_blocks",
  "rules": [
    { "policy": "keep", "match": [] },
    { "policy": "float8_e4m3fn",  "match": ["img_mod.1", "txt_mlp.net.0.proj", "txt_mlp.net.2", "txt_mod.1"] },
    { "policy": "nvfp4","match": ["attn.to_k", "attn.to_q", "attn.to_v", "attn.to_out.0", "img_mlp.net.0.proj", "img_mlp.net.2"] }
  ]
}

How to Reproduce

You need nVidia GPU and around 40GB RAM.

Download https://github.com/bedovyy/comfy-dit-quantizer
activate python environment from ComfyUI.
quantize.py configs/qwen-image-edit-2511.json <SOURCE> uncalibrated.safetensors
add_input_scale.py calibs/qwen-image-edit-2511.json uncalibrated.safetensors <TARGET>

Library: diffusion-single-file
License: apache-2.0
Created: Jun 16, 2026
Updated: Jun 16, 2026