Instructions to use BennyDaBall/PiD-1.5-qwenimage-nvfp4-comfy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusion Single File
How to use BennyDaBall/PiD-1.5-qwenimage-nvfp4-comfy with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
π PiD 1.5 qwenimage β NVFP4 (ComfyUI-ready)
The first quantized PiD decoder on HF. 2.61 GB β 1.09 GB, drops straight into a stock
UNETLoader, and decodes a 33 MP master in 16 s on a 5090 (bf16 takes 20). No custom
loader. No core patches. No Blackwell requirement either β this runs anywhere the bf16 file
runs.
π§ What is this?
NVIDIA's PiD v1.5 decoder for the qwen-image latent family β the 4-step pixel-diffusion decode that replaces your VAE decode and hands back 4Γ the resolution. Same decoder, 42% of the size, a little faster.
Everyone else ships this model in bf16 only. Not anymore.
π Same seed, same latent, both builds
100% crops β faces, lettering, bokeh all hold:
π Specs
| Attribute | Details |
|---|---|
| Base | nvidia/PiD v1.5 qwenimage (4-step distill), via the Comfy-Org/PixelDiT repackage |
| Quantization | NVFP4 (group 16), quality-critical layers kept bf16 |
| File size | 1.09 GB (bf16: 2.61 GB) |
| Requirements | ComfyUI β₯ 0.32 (tested on 0.33.0) Β· any GPU that runs PiD bf16 |
| Text encoder | gemma_2_2b_it_elm_bf16.safetensors from Comfy-Org/PixelDiT (CLIPLoader type pixeldit) |
π» Usage
Drop the model in ComfyUI/models/diffusion_models/, select it in UNETLoader, done. Two
workflows included:
Simple (core nodes only) β PiD-1.5-qwenimage-nvfp4_simple_1mp_to_16mp.json. Stage-1
render at ~1MP β single-shot PiD 4Γ β 5376Γ3072, built from nothing but core nodes
(PiDConditioning + a 4-step KSampler). Drop the included pixel_space_vae.safetensors into
ComfyUI/models/vae/ for the final decode step. Keep this one near its trained envelope β
single-shot PiD collapses past ~4K output.
Tiled (the big guns) β PiD-1.5-qwenimage-nvfp4_tiled_2mp_to_33mp.json. Stage-1 β
seam-free 7680Γ4352 in one queue via
ComfyUI-Latent-Tiled-PiD:
install from ComfyUI Manager (search "Latent-Tiled-PiD") or the
Comfy Registry.
Every included workflow was executed through the actual ComfyUI frontend against this exact file before upload. qwen-family latents only β the FLUX.2 build is here.
βοΈ License & credits
NVIDIA created PiD (paper); Comfy-Org published the bf16 ComfyUI repackage this converts. NSCLv1 β non-commercial research/evaluation use only, derivatives included. Read the nvidia/PiD card before you build anything on it. Not affiliated with NVIDIA or Comfy-Org. Conversion and validation by BennyDaBall_OG.
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