--- 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 ๐ฆ 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 โ 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.๐ฆ  --- **Important notes**: This version is exclusively designed around the **Klein 9B accelerated edition** โ 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 โ more natural, and truly unstoppable! ๐ฆ 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.  --- # Dark Beast KLEIN 9b ๐ฆ 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 ๐ฆ 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 โ breathtaking high-quality images in just 5 steps โก Recommended settings: 5 steps, CFG=1 (fixed), any seed you want In one sentence: Taking Kleinโs already blazing speed and cranking it to absolute BlitZ velocity while keeping every drop of that ferocious Dark Beast soul! ๐ฆ Lightning-fast generation awaits โ unleash it now! ๐ 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! ๐ ้ๅธธๆ่ฐข [@alcaitiff](https://civitai.com/models/2348977/klein-9b-unchained-xxx) ๅฏน Zimage ๅ Klein 9b ็ๆจกๅ่ฎญ็ปๅๅบ็ๆฐๅบ่ดก็ฎ!
