---
license: other
license_name: bluepixel-component-licenses
license_link: https://huggingface.co/t8star/BluePixel-Comfy/blob/main/LICENSE.md
language:
  - en
  - zh
base_model: openvivo/BluePixel-Turbo
base_model_relation: quantized
pipeline_tag: image-to-image
library_name: comfyui
tags:
  - comfyui
  - bluepixel
  - image-editing
  - int8
  - convrot
  - 4k
  - safetensors
---

# BluePixel for ComfyUI

**English** | [简体中文](README_CN.md)

Three standalone components converted from [openvivo/BluePixel-Turbo](https://huggingface.co/openvivo/BluePixel-Turbo) for native ComfyUI image editing. Use them with [ComfyUI BluePixel T8](https://github.com/T8mars/Comfyui-BluePixel-T8), which provides the loaders and eight editable canvas workflows.

## Download

Place each file in the matching folder under your ComfyUI installation. Total download: **28.19 GB** (decimal).

| Component | File | ComfyUI folder | Size |
| --- | --- | --- | --- |
| Diffusion · INT8 ConvRot | [bluepixel_turbo_int8_convrot.safetensors](diffusion_models/bluepixel_turbo_int8_convrot.safetensors) | `models/diffusion_models/` | 9.09 GB |
| Qwen3-8B · BF16 | [bluepixel_qwen3_8b_original.safetensors](text_encoders/bluepixel_qwen3_8b_original.safetensors) | `models/text_encoders/` | 16.39 GB |
| DCAE-F64 · FP32 | [bluepixel_dcae_f64.safetensors](vae/bluepixel_dcae_f64.safetensors) | `models/vae/` | 2.71 GB |

Each component is one Safetensors file. The text encoder includes its tokenizer. File sizes and SHA256 hashes are recorded in [checksums.json](checksums.json); adjacent manifests document conversion mappings and source hashes.

## Quick start

1. Install **BluePixel T8** through ComfyUI Manager, or follow the [manual installation guide](https://github.com/T8mars/Comfyui-BluePixel-T8/blob/main/README_EN.md#installation).
2. Download all three components above and restart ComfyUI.
3. Download the JSON for a [1K preview or 4K editing workflow](https://github.com/T8mars/Comfyui-BluePixel-T8/tree/main/workflows), select the files and input image, and enter an editing instruction. Open the local canvas JSON with **Ctrl+O**, or drop it onto ComfyUI.
4. Start with **4 steps, CFG 3**. The 4K example outputs 4096×4096.

Requires Python 3.10+, ComfyUI 0.43.0+, Diffusers 0.40+ and a compatible PyTorch / comfy-kitchen CUDA environment. Use the package's three **BluePixel Loader** nodes, then connect their standard outputs to ComfyUI sampling and VAE nodes. DCAE-F64 has 64× spatial compression and cannot be replaced by an ordinary Flux2 VAE.

## Conversion and validation

- Source weights: `openvivo/BluePixel-Turbo` at `e9c7a641a4bcd9851eef50c1ce9b07fa44f6044c`.
- Diffusion weights are mapped to the native Flux2/Klein layout and quantized with INT8 ConvRot. Quantization is lossy; this is not a BF16-equivalent checkpoint.
- Qwen3 retains its original precision; DCAE is stored in FP32. No additional training or LoRA is applied to this release.
- Initial model validation included 107 unit tests and eight complete inference paths, an actual 4K edit and text-encoder / VAE comparisons. See [validation conditions and measured differences](https://github.com/T8mars/Comfyui-BluePixel-T8/blob/main/docs/validation.md).

Speed, memory requirements and output quality depend on hardware and task. Download size is not a VRAM requirement. These files are intended for the linked ComfyUI integration; they are not a drop-in Diffusers pipeline directory.

## License and attribution

Weights retain their component-specific upstream terms. The diffusion model derives from FLUX.2 Klein 9B and is subject to the **FLUX Non-Commercial License**. The upstream BluePixel repository also supplies an OpenAtom model license; Qwen3 and DCAE are attributed under Apache-2.0. The upstream model card's Apache metadata does not replace the base-model restrictions.

Read [LICENSE.md](LICENSE.md), [NOTICE](NOTICE) and the preserved files in [licenses](licenses) before use. This conversion does not grant additional commercial rights. The node repository's GPL license applies to its code, not these weights.

Credits: vivo BluePixel, Black Forest Labs, Qwen, NVIDIA DCAE, ComfyUI and comfy-kitchen. Converted and packaged by T8star.

## T8star

[Bilibili](https://space.bilibili.com/385085361) · [YouTube](https://www.youtube.com/@T8star-Aix/) · [API](https://api.seedance.nz/sign-up?aff=5f4w) · [Free gallery](https://www.openzhenzhen.com) · [Online AI apps](https://www.runninghub.ai/zh-cn/user-center/1907375370302308353/userPost?inviteCode=rh-v1121) · [ComfyUI bundle](https://pan.quark.cn/s/264edb7e36bd) · [Hugging Face](https://huggingface.co/t8star)