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PiD-1.5-flux2-nvfp4-comfy
BennyDaBall/PiD-1.5-flux2-nvfp4-comfy
PiD-1.5-flux2-nvfp4-comfy is a image-to-image model from BennyDaBall. Use it when you need one image transformed into another. It is set up for diffusion-single-file. The card lists the license as other.
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Repo size
1.1 GB
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.safetensors1.1 GB · 99%
At a glance
- Task
- Image-to-Image
- Library
- diffusion-single-file
- License
- other
- Access
- Public
- Created
- Aug 17, 2026
- Updated
- Nov 9, 2026
- SHA
- 428fc904
Base models
Model card
From the Hugging Face model README
🚀 PiD 1.5 FLUX.2 — NVFP4 (ComfyUI-ready)
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The FLUX.2 half of the first quantized PiD decoder pair on HF. 2.61 GB → 1.09 GB,
drops straight into a stock UNETLoader, decodes faster than the bf16 original. No custom
loader. No core patches. No Blackwell requirement either — this runs anywhere the bf16 file
runs.
🧠 What is this?
NVIDIA's PiD v1.5 decoder for the FLUX.2 latent family (FLUX.2 dev + Klein 4B/9B, 128-channel latents) — the 4-step pixel-diffusion decode that replaces your VAE decode and hands back 4× the resolution. Same decoder, 42% of the size, a little faster.
Running qwen-image models instead? That build is already out: PiD-1.5-qwenimage-nvfp4-comfy.
👀 Same seed, same latent, both builds
100% crops — faces, lettering, bokeh all hold:
📋 Specs
| Attribute | Details |
|---|---|
| Base | nvidia/PiD v1.5 flux2 (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 ≥ 0.32 (tested on 0.33.0) · any GPU that runs PiD bf16 |
| Text encoder | gemma_2_2b_it_elm_bf16.safetensors from Comfy-Org/PixelDiT (CLIPLoader type pixeldit) |
💻 Usage
Drop the model in ComfyUI/models/diffusion_models/, select it in UNETLoader, done. Four
workflows included — pick your Klein and your size:
Simple (core nodes only) — PiD-1.5-flux2-nvfp4_simple_klein4b_1mp_to_16mp.json and
..._simple_klein9b_1mp_to_16mp.json. Klein stage-1 at ~1MP → single-shot PiD 4× →
5376×3072, 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 these near the trained envelope — single-shot PiD collapses past ~4K output.
Tiled (the big guns) — PiD-1.5-flux2-nvfp4_tiled_klein4b.json and
..._tiled_klein9b.json. Stage-1 → seam-free 7680×4352 in one queue via
ComfyUI-Latent-Tiled-PiD:
install from ComfyUI Manager (search "Latent-Tiled-PiD") or the
Comfy Registry. Klein 9B stays coherent
up to the ~59 MP rungs; let 4B own the monsters.
Every included workflow was executed through the actual ComfyUI frontend against this exact
file before upload. FLUX.2-family latents only (128-ch; the nodes auto-detect them under
flux/flux2).
⚖️ License & credits
NVIDIA created PiD (paper); Comfy-Org published the bf16 ComfyUI repackage this converts. NSCLv1 — 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.
Follow me on X @BennyDaBall_OG !
Want to support my work? Buy me a coffee on Ko-fi !
- Task
- Image-to-Image
- Library
- diffusion-single-file
- License
- other
- Created
- Aug 17, 2026
- Updated
- Nov 9, 2026