Team Ai
Modelpublic

QuantFunc/Nunchaku-Qwen-Image-2512

sourceHugging Faceapache-2.0updated 4mo agoView on Hugging Face
90likes2.4kdownloads
Model Card

<!-- QF-LICENSE-BLOCK:START -->

License & Attribution

These are quantized derivative weights of `Qwen/Qwen-Image-2512` (Qwen-Image-2512).

  • —Modifications: the original weights were quantized (e.g. W4A4 / FP4 / INT4 / FP8) and repackaged for the QuantFunc inference engine — a "modification" under Apache-2.0 §4(b).
  • —License: Apache License 2.0 (inherited from the base model), included as `LICENSE`. Upstream copyright and attribution notices are retained.
  • —This repository is not affiliated with or endorsed by the upstream model authors.
Disclaimer: "Nunchaku" / "SVDQuant" name the quantization method/format (the open-source SVDQuant work by MIT HAN Lab, Apache-2.0). This repository is an independent re-quantization and is not affiliated with, sponsored by, or endorsed by MIT HAN Lab or the Nunchaku project. Official Nunchaku releases are under the nunchaku-ai / nunchaku-tech namespaces.

<!-- QF-LICENSE-BLOCK:END -->

QuantFunc

<div align="center" style="margin-top: 50px;"> <img src="assets/logo.webp" width="300" alt="Logo"> </div>

<p align="center"> 🤗 <a href="https://huggingface.co/QuantFunc">Hugging Face</a> &nbsp;|&nbsp; 🤖 <a href="https://www.modelscope.cn/profile/QuantFunc">ModelScope</a> &nbsp;|&nbsp; 💻 <a href="https://github.com/RealJonathanYip/ComfyUI-QuantFunc">GitHub</a> &nbsp;|&nbsp; 💬 <a href="#wechat">WeChat (微信)</a> &nbsp;|&nbsp; 🎮 <a href="https://discord.gg/jCp9TpFWcn">Discord</a> </p>

⚡ Qwen-Image-2512 — SVDQ (Nunchaku) pre-quantized text-to-image. 2x–11x faster with the QuantFunc plugin; 100% Nunchaku-ComfyUI compatible.

Offline-quantized Qwen-Image-2512 text-to-image checkpoints in best-quality / balanced / ultimate-speed variants (INT4 & FP4), ready to drop straight into ComfyUI.

Powered by the [QuantFunc ComfyUI plugin](https://github.com/RealJonathanYip/ComfyUI-QuantFunc) — the fastest diffusion inference engine:

  • —🚀 2x–11x speedup over standard BF16/FP16 Python pipelines (pre-exported → even faster loading).
  • —⚙️ Native C++/CUDA (libquantfunc.so / quantfunc.dll) with zero Python model dependencies.
  • —🧩 Dual engine (SVDQ offline + Lighting runtime 4-bit), zero-cost LoRA stacking, reference-image editing & inpainting.
  • —🟢 Full GPU coverage — RTX 20/30/40/50 · A100/H100/H200/B100/B200/GB300 · RTX 6000 Ada / PRO Blackwell (CUDA 12 & 13); native FP4 on Blackwell.

👉 Install the plugin: https://github.com/RealJonathanYip/ComfyUI-QuantFunc

Introduction

We are excited to share our latest model series based on <strong>nunchaku + qwen-image-2512</strong> quantization. These models are carefully optimized to maintain high-quality output while significantly improving inference speed and efficiency. <strong>All models are 100% compatible with the nunchaku-comfyui && lora plugin</strong> and can be used directly in ComfyUI.

Gallery

<div align="center">

<table> <tr> <td align="center"><img src="assets/ComfyUI00006.png" alt="Result 6" style="max-width: 300px;"></td> <td align="center"><img src="assets/ComfyUI00010.png" alt="Result 3" style="max-width: 300px;"></td> </tr> <tr> <td align="center"><img src="assets/ComfyUI00019.png" alt="Result 1" style="max-width: 300px;"></td> <td align="center"><img src="assets/ComfyUI00051.png" alt="Result 2" style="max-width: 300px;"></td> </tr> <tr> <td align="center"><img src="assets/ComfyUI00040.png" alt="Result 4" style="max-width: 300px;"></td> <td align="center"><img src="assets/ComfyUI00048.png" alt="Result 5" style="max-width: 300px;"></td> </tr> </table>

</div>

Model Checkpoints

Namelow_rankNotes
nunchakuqwenimage2512bestqualityfp4256Best quality model, suitable for scenarios with extremely high quality requirements
nunchakuqwenimage2512bestqualityint4256Best quality model, suitable for scenarios with extremely high quality requirements
nunchakuqwenimage2512ultimatespeedint432Ultimate speed model, prioritizing inference speed
nunchakuqwenimage2512ultimatespeedfp432Ultimate speed model, prioritizing inference speed
nunchakuqwenimage2512balance_int4128Balanced model, achieving the best balance between quality and speed
nunchakuqwenimage2512balance_fp4128Balanced model, achieving the best balance between quality and speed

4 steps workflow

Here’s a <a href="https://huggingface.co/QuantFunc/Nunchaku-Qwen-Image-2512/tree/main">workflow</a> example of integrating 4-step LoRA in ComfyUI. If you don’t need 4-step LoRA, simply remove the LoRA node. <img src="assets/workflow_image.png" alt="work flow" style="max-width: 800px;">

Coming Soon

If you encounter any issues during use, feel free to join our community for feedback:

  • —Join our Discord server
  • —Scan the QR code below to join our WeChat group

We will add support for build in lora and qwen-image-edit-2511 in approximately one month.

<div align="center" id="wechat"> <img src="https://raw.githubusercontent.com/RealJonathanYip/ComfyUI-QuantFunc/main/assets/WeChat.jpg" alt="WeChat Group" style="max-width: 300px;"> </div>