| --- |
| license: other |
| license_name: qwen-research |
| license_link: https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE |
| pipeline_tag: text-to-image |
| tags: |
| - comfyui |
| - qwen-image-2.1 |
| - text-to-image |
| - image-to-image |
| - image-generation |
| - quantized |
| - qwen |
| - image-generation |
| - image-editing |
| - rgba |
| base_model: Qwen/Qwen-Image-2.1 |
| base_model_relation: quantized |
| --- |
| |
| ## About these variants |
|
|
| Four precision levels are available for Qwen-Image-2.1, trading VRAM and speed against generation quality: |
|
|
| - **BF16** — full-precision reference (~14 GB). Highest quality, largest footprint. |
| - **INT8 (W8A8)** — 8-bit weights + 8-bit activations (~7 GB). Near-lossless quality, ~2× smaller than BF16, runs on INT8 tensor cores (RTX 30-series and up). |
| - **INT6 (W6A8)** — 6-bit weights + 8-bit activations (~5.5 GB). Middle-ground: smaller than INT8 with only a small quality trade-off. |
| - **INT4 (W4A8)** — 4-bit weights + 8-bit activations (~4 GB). Smallest footprint; uses ConvRot with a per-tensor codebook that decodes to INT8 for compute, so it runs on the same INT8 hardware as W8A8. Larger quality trade-off than INT6. |
|
|
| # Qwen-Image-2.1 7B — INT4 (W4A8) & INT6 (W6A8) ConvRot for ComfyUI |
|
|
| INT4 and INT6 quantized weights of **Qwen-Image-2.1** for fast, low-VRAM inference in ComfyUI. |
|
|
| This is a modified (quantized) version of the Qwen-Image-2.1 model. It is not an official Qwen release and is not endorsed by the Qwen team. |
|
|
| ## About Qwen-Image-2.1 |
|
|
| A unified text-to-image generation and image editing model in the Qwen family. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Qwen-Image-2.1 balances generation quality, inference efficiency, and versatility. |
|
|
| ### Highlights |
|
|
| - **Efficient Image Generation** — combines strong visual performance with fast inference and a compact design, making high-quality image creation accessible across a wide range of creative workflows. |
| - **Flexible Creative Control** — supports diverse inputs, outputs, and localized edits, giving creators the flexibility to explore ideas and refine details within a unified workflow. |
|
|
| ### Key improvements in 2.1 |
|
|
| - **Compact and Efficient** — lightweight architecture with mixed-granularity attention and prefix KV cache reuse delivers strong image quality at low computational cost. |
| - **Native Transparency, Unified Creation and Editing** — generate regular or transparent (RGBA) images from text, edit transparent layers, and extract subjects from photographs — all in one model. |
| - **Versatile Editing** — support up to 10 reference images, specify local edits via circles, painted annotations, or separate masks, and preserve identity for people and products. |
| - **Realistic Textures and Refined Aesthetics** — improved typography, portrait lighting, and fine details for more visually compelling results. |
|
|
| ## License |
|
|
| Qwen-Image-2.1 is licensed under the [Qwen Research License](https://huggingface.co/Qwen/Qwen-Image-2.1/blob/main/LICENSE). These files are a quantized derivative and are distributed under the same license — see the original repository for full terms, permitted uses, and any commercial-use restrictions. |
