Flux2-Klein-9B-True-V2
针对低显存的用户，推荐 smthemex/ComfyUI_UniBlockSwap，只需 4-6GB 显存，即可跑 bf16 全量模型。 Recommend smthemex/ComfyUI_UniBlockSwap plugin for LOW VRAM users, it only requires 4-6GB of VRAM to run the full bf16 model.
您可以尝试一下全新的 ComfyUI GGUF 模型加载插件 smthemex/ComfyUI_Dif_GGUF，它能适配更多的 GGUF 文件格式，并且将很快集成低显存(4-8GB)显卡的 GGUF 模型块卸载管理能力。 Recommend to try the new GGUF ComfyUI loader plugin, smthemex/ComfyUI_Dif_GGUF, it compatible with more GGUF format, and will add low VRAM (4-8GB) management for GGUF soon.
V2 版本模型在 FLUX.2-Klein-9B-True-V1 的基础上再次进行了全量微调，相比 V1 模型，在如下方面得到了改善和提升：
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图像的真实感和质感进一步改善，基本接近香蕉(Nano Banana)的水平。
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提示词遵循和还原能力，参数适配性和LoRA兼容性进一步改善，。
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成图结构更归整、合理，美学方面也有一些改善。
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图像编辑能方面，提示词遵循更好，偏移和偏色也有一些改善。
具体效果参见如下对比图片。
The V2 version of this model has undergone a full fine-tuning based on FLUX.2-Klein-9B-True-V1. Compared to the V1 version, it has some improvements and enhancements as below:
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The realism and texture of images have been further improved, basically reaching the level of Nano Banana.
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Prompt adherence and restoration capability, parameter adaptability, and LoRA compatibility have been further enhanced.
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The image structure is more organized and reasonable, with some aesthetic improvements as well.
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In image editing ability, prompt adherence is better, pixel shift and color bias have also seen some improvements.
For specific results, please refer to the comparison images as below:
使用方法：
与版本 V1 使用方法相同。
The same with V1 vesrion.
可以使用 Turbo / Distill LoRA 加速，但加速会影响画质，尽可能使用较小的 LoRA Weight 适配。
for Turbo Lora : anyMODE's rank128 / rank64 Civitai or Huggingface, weight 0.2 - 0.3 for steps 4 - 8.
for Distill LoRA : vafipas663's rank128 / rank256 Huggingface, weight 0.4 - 0.6 for steps: 4 - 8.
针对编辑后图像会有偏色等问题，推荐使用 ComfyUI-LCS 插件进行 Lentent 修正。
for Color and Shape correct of Image, you can use plugin of : ComfyUI-LCS
Also on: Modelscope.cn
模型许可：
本模型请在遵循 black-forest-labs 公司非商业许可 (FLUX Non-Commercial License) 下使用。
This model falls under the FLUX Non-Commercial License.