| --- |
| license_name: flux-non-commercial-license |
| license_link: LICENSE.md |
| base_model: |
| - black-forest-labs/FLUX.2-klein-9B |
| base_model_relation: finetune |
| tags: |
| - flux |
| - klein |
| - blitz |
| - finetune |
| - comfyui |
| - flux2 |
| --- |
| # Dark Beast KLEIN 9b 🟦 V2 BFS 03/03/2026 |
|
|
| This is the **next-level face-swap** specialized evolution of the **Dark Beast** lineage, built on the lightning-fast **FLUX.2 Klein 9B** accelerated model from **Black Forest Labs**. |
|
|
| Engineered with targeted optimizations for face swapping practices, it integrates **BFS (Best Face Swap)** technology to completely eliminate the rigid, unnatural look that plagued earlier face replacements — delivering seamless, lifelike integrations with preserved identity, expression, and lighting. |
|
|
| It also fully fixes the portrait reference issue from the previous **DB BlitZ** versions, ensuring right reference adherence every time. |
|
|
| Special thanks to the scheme provider: [https://github.com/alisson-anjos](https://github.com/alisson-anjos) for the powerful BFS foundation that powers this breakthrough.🟦 |
|
|
|
|
|  |
|
|
| --- |
|
|
| **Important notes**: |
|
|
| This version is exclusively designed around the **Klein 9B accelerated edition** — no base model exists. |
|
|
| Usage is identical to **Black Forest Labs'** official FLUX.2 **Klein 9B accelerated** release: ultra-low steps (e.g., **4-5**), **CFG=1** fixed, blazing inference speed on consumer hardware. |
|
|
| In one sentence: Dark Beast's ferocious soul meets **BFS (Best Face Swap)** technology — more natural, and truly unstoppable! 🟦 |
|
|
| for more infomation about **BFS (Best Face Swap)** : |
|
|
| [https://huggingface.co/Alissonerdx](https://huggingface.co/Alissonerdx) |
|
|
| Alternatively, it can be directly applied to the entire Klein 9b/Qwen Edit base and Fine-tune models, through **LoRA Adapter** parameter injection. |
|
|
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|
|  |
|
|
| --- |
|
|
| # Dark Beast KLEIN 9b 🟦 V1.5 BlitZ lora adapter 02/16/2026 |
|
|
| DarkBeast5steps_extracted_lora_r256 uploaded |
| |
| working fine with FLUX.2 Klein 9b models |
| |
| --- |
| |
| # Dark Beast KLEIN 9b 🟦 V1.5 BlitZ 02/08/2026 |
| |
| Fine-tunning of [black-forest-labs/FLUX.2-klein-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-9B) with BF16\FP8e4m3fn\NVFP4 quantization. |
| |
| And Merge with @alcaitiff [klein-9b-unchained-xxx](https://civitai.com/models/2348977/klein-9b-unchained-xxx) |
| |
| This is the ultimate speed-optimized Dark Beast V1 evolution, based on Flux.2 Klein 9B, |
| |
| engineered specifically for lightning-fast low-step + CFG=1 workflows (5steps). |
| |
| Also available in NVFP4 quantized format, optimized for acceleration on Blackwell architecture GPUs. |
| |
| （ like RTX50XX, PRO6000, B200, and others ） |
| |
| Also supports non-50 series GPUs (automatic 16-bit operation), Verify environment is my ComfyUI 0.11 |
| |
| |
| ## Key features: |
| |
| Fully preserves the signature Dark Beast style, rich details, and intense Black Beast |
| aesthetic from the standard lineage |
| |
| Refined through advanced targeted distillation & fine-tuning, now perfectly dialed |
| in for zero-CFG guidance at minimal steps |
| |
| BlitZ-level inference speed — breathtaking high-quality images in just 5 steps ⚡ |
| |
| Recommended settings: 5 steps, CFG=1 (fixed), any seed you want |
| |
| In one sentence: Taking Klein’s already blazing speed and cranking it to absolute BlitZ |
| velocity while keeping every drop of that ferocious Dark Beast soul! 🟦 |
| |
| Lightning-fast generation awaits — unleash it now! 🚀 |
| |
| |
| Usage: |
| ``` |
| pip install sdnq |
| ``` |
| |
| ```py |
| import torch |
| import diffusers |
| from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers |
| from sdnq.common import use_torch_compile as triton_is_available |
| from sdnq.loader import apply_sdnq_options_to_model |
| |
| pipe = diffusers.Flux2KleinPipeline.from_pretrained("GuangyuanSD/FLUX.2-klein-9B-Blitz-Diffusers", torch_dtype=torch.bfloat16) |
| |
| # Enable INT8 MatMul for AMD, Intel ARC and Nvidia GPUs: |
| if triton_is_available and (torch.cuda.is_available() or torch.xpu.is_available()): |
| pipe.transformer = apply_sdnq_options_to_model(pipe.transformer, use_quantized_matmul=True) |
| pipe.text_encoder = apply_sdnq_options_to_model(pipe.text_encoder, use_quantized_matmul=True) |
| # pipe.transformer = torch.compile(pipe.transformer) # optional for faster speeds |
| |
| pipe.enable_model_cpu_offload() |
|
|
| prompt = "A cat holding a sign that says hello world" |
| image = pipe( |
| prompt=prompt, |
| height=1024, |
| width=1024, |
| guidance_scale=1.0, |
| num_inference_steps=4, |
| generator=torch.manual_seed(0) |
| ).images[0] |
| |
| image.save("flux-klein-Blitz.png") |
| ``` |
| |
| Original BF16 vs Blitz fine-tune comparison: |
| |
| | Quantization | Model Size | Visualization | |
| | --- | --- | --- | |
| | Original BF16 | 18.2 GB |  | |
| | Blitz fine-tune | 18.2 GB |  | |
| |
| |
| Big thanks to @alcaitiff for the awesome work and killer contributions to training Z-Image and Klein models! Seriously impressive stuff! 🚀 |
| |
| 非常感谢 [@alcaitiff](https://civitai.com/models/2348977/klein-9b-unchained-xxx) 对 Zimage 和 Klein 9b 的模型训练做出的杰出贡献！ |
